What the Future Holds for Virtual Staffing?

Whether you're looking for an AI-powered virtual assistant, Business process outsourcing, or chatbots to help with your daily tasks, it's possible that a VA could be the solution to your company's needs. While AI-powered virtual assistants and Chatbots are great, they won't replace human skills, so the future of virtual staffing lies in the human and business interaction between them.

AI-powered virtual assistants

Artificial intelligence-powered virtual assistants (IVAs) can help companies with a variety of tasks. They can improve customer support, reduce the number of calls to human agents, and process repetitive tasks so that employees can focus on more complex tasks. AI assistants can also collect and process data - traditionally, customer support data requires an analyst to sift through hours of data to find the relevant details.

Voice-assistants can break down social barriers by enabling employees to engage with customers via a conversation rather than relying on typing. Many GM Financial employees reported increased job satisfaction with the new solution, which reduced their workload and required fewer staff. With a growing number of companies conducting business online, voice-assisted customer service is the solution of choice. In fact, 79% of contact center leaders plan to invest in greater AI capabilities over the next two years.

Business process outsourcing

The practice of outsourcing company functions is known as business process outsourcing. Businesses will hire a third party to perform the tasks that do not require their core competencies. The third party can be based in the same country or a different one. Examples of non-core tasks that a virtual assistant (VA) can perform include data entry, customer service, research, graphic design, software development, and personal services. This method of outsourcing can be a highly efficient way to hire additional staff for a business.

Businesses of any size can benefit from the services provided by virtual staffing. A small restaurant, for example, has employees in the kitchen, the waiting area, and preparing drinks. These functions can be broken down into specialized tasks that require specialized skills. Virtual staffing can help this restaurant save money by bringing in qualified individuals who can perform these tasks more efficiently. The same is true for companies with large amounts of information to analyze.

Chatbots

AI-based chatbots can help you out with customer service. This type of technology is based on intelligent personal assistants such as Siri and Google Home. These artificial intelligence systems can understand nuances of human language, and are capable of making appointments and understanding moods. They are far more sophisticated than chatbots, which are based on architecture and models that are designed to respond to questions. Moreover, chatbots can be operated without a dedicated team.

A good chatbot should be able to use stored data to automate mundane tasks and maintain situational awareness. Additionally, bot conversations should be short and easy to understand. To achieve this, chatbots should not use graphics, and should be able to store conversation histories for further reference. If possible, users should be able to program the chatbot to respond to a question or request in multiple texts. However, bots should also be capable of storing conversations to improve their efficiency.

Cost

The cost of hiring a virtual assistant varies depending on the skillset and experience level of the individual you hire. Virtual assistants can perform a variety of administrative duties, including fielding calls after hours, generating traffic for your online storefront, and handling financial projects. Some VAs specialize in specific areas, such as invoice processing, vendor relations, and receipt transcription. These virtual assistants can also help you with general administrative tasks, such as scheduling travel and type notes and documents.

Project-based packages are often more expensive than hourly rates, as VAs may have specific skills that you don't need. If you're planning a one-off project, a VA can input contacts into your email marketing platform, craft email copy, monitor bounce-backs, and more. However, if you have a large budget, a project-based package is worth considering. You'll pay at least half of the total cost up front and the rest when the project is complete.

#virtualassistant #staffing #recruitment #recruiting #recruiter 

3 Mistakes That Make Good Employees Leave

As per a new report, over 70% of U.S. laborers are thinking about or effectively searching for a new position.

Losing a top worker is each director's bad dream, particularly in a tight work market. Putting forth attempts to further develop representative maintenance should be high on each organization's need list.

So what makes a decent worker leave, and would it be able to be forestalled?

No Work/Life Balance

As an administrator, it's not difficult to work your best individuals the hardest. All things considered, they set forth the most energy and make you look great. Then again, the worker can feel like they are being rebuffed for their usefulness.

Be resolute about work/life balance. While it's occasionally important to answer an email or call outside of the workplace, it ought not be a propensity. We as a whole need time to re-energize. Assist your group with making an unmistakable partition among work and home. They will see that you esteem their opportunity and will return to work every day revived and all set.

(Remember that you show others how its done. Assuming you're routinely working almost to excess or shooting off messages night-time, your representatives will see that as the assumption. Deal with yourself, as well.)

Few Opportunities for Growth

Indeed, even the coolest organization advantages start to lose their allure when representatives don't feel like they are developing as an expert. Top representatives need to be enlivened and afterward get the valuable chance to follow up on that motivation. It's the supervisor's liability to keep recognizing regions in which their immediate reports can grow their range of abilities. Great administrators make due, regardless of how skilled their immediate report might be. They focus and are continuously giving criticism.

Consider executing an inside recruiting process in the event that you don't as of now have one. Show an inclination for hiring inside. This permits confided in specialists inside your association to propel their professions and progress up the stepping stool. Recruiting inside likewise definitely brings down the expense of an all out employing search.

Keeping great representatives requires steady consideration and care, similar as maintaining a business. Be mindful of the requirements of your representatives to make shared trust and regard. It is generally difficult, however the prizes are really great for business.

Lack of Communication

Absence of correspondence, under-correspondence, miscommunication… Whatever you need to call it, it's a far and wide issue. It breeds vulnerability and sabotages the certainty of good representatives. They start to re-think themselves and feel that they can't confide in one another - or their chiefs besides.

Significant correspondence isn't giving an explanation. It is a discourse intended to arrive at shared belief for the two sides. Instead of passing down in a mandate, urge your immediate reports to partake in the dynamic interaction whenever the situation allows. Be available to groundbreaking thoughts. Advance fair conversations inside your Company.

Great representatives are an interest in your organization's future, yet you don't keep them coincidentally. Deal with individuals that deal with you and watch your most significant organization venture pay off.

#company #staffing #recruitment #recruiting #recruiter #hire #hiring #usa

The Heat Index Of Questions About PHP

PHP (Hypertext Pre-processor) is a popular server-side scripting language mainly used for developing websites and web applications. It can be used to build either static or dynamic websites. It is very simple and easy to learn. So, today we will be checking out the 11 most frequently asked questions about PHP.

11 Most Asked Questions About PHP

1. How to prevent SQL injection in PHP?

2. How to check if a string contains a specific word?

3. Why not to use mysql_* functions in PHP?

4. How to delete an element from an array in PHP?

5. Is there any way to use PHP and cURL to get the associated thumbnail from the YouTube API?

6. When to use self over $this?

7. How to get PHP errors to display?

8. How to write two functions that would take a string and return if it starts with the specified character/string or ends with it?

9. How to make a redirect in PHP?

10. How do you use bcrypt for hashing passwords in PHP?

11. How to use PHP to get the current year?

#php #programming #coding #recruiting

How To Create Testing Portfolios In GitHub Platform: Essential Tips

Software testers travel a varied road: some love writing code and automating otherwise tedious testing tasks, while others enjoy strategic exploration of software to find the trickiest bugs, doing things that “no user would ever try”. Many enjoy a balance of both. Almost all software testers that I know suffer in one area: a living portfolio of work that they are able to present and discuss with hiring managers.

Developers have a lot more visibility in the github ecosystem to build a portfolio: their work necessitates frequent interaction with the platform, and developers have more obvious choices when it comes to showing their skills in the github medium. Many job postings for software developers and software testers ask for the applicants to share their github username, so that hiring managers can review their portfolio. Software testers are asked for this information, but the path forward (What should be included? What matters? Where do I even begin?) is daunting, at best.

I know, because I was one of those testers. I had heard, mostly from developers, to “go look for a project and find a way to contribute”. When I was a software tester, I couldn’t readily determine what contributions would be helpful to a project.

#github #testing #recruiting

4 Things To Consider When Hiring a Data Scientist

As a staffing agency with one of our specialties being Data Science, we know what to look out for when hiring Data Science talent.

Data Science is still one of the buzzwords in technology in 2020, but let’s go back in time and see where it all started.

In 2012, the Harvard Business Review (HBR) said that the data scientist role was the sexiest job in the 21st century. Close to a decade later, it’s arguably even sexier.

LinkedIn ranked it third on its 2020 list of emerging jobs with a 37% annual growth rate. With artificial intelligence (AI) and big data now a part of our daily conversations, it’s impossible to envision a world where data science dies off. This is where everyone’s focus is. It’s no wonder this role made it on Indeed.com’s “Best Roles in 2020” list.

So we know that the demand is there, the question is: What do you look for when hiring a Data Scientist, and who are you competing with?

How much you should budget for a Data Scientist.

Well, several factors affect the salary you can expect to pay for a data science role. One of the biggest contributors is, as you’d expect, their skill set. Essentially, how can they deliver ROI?

The issue with data science is that there aren’t enough qualified candidates to fill the open positions (even in the tough economy). In a candidate-driven market, it is hard to find cream de la creme Data Scientist, and in the employer-driven market, you can waste hours sorting through unqualified resumes to land on a few worth interviewing.

There are hundreds of candidates with the title but lacking the skills to match. In 2011, McKinsey Digital estimated there would be a shortage of around 140,000–190,000 data scientists by 2018. And they were right. In 2018, LinkedIn reported there was a shortage of 151,717 data scientists.

But this is where the good news comes in —** when the applicants with the right qualifications come up, they have much more negotiating power. They can secure high salaries with great benefits.**

In the U.S., most data scientists (54%) have at least a master’s degree, with 23% holding a doctorate. They typically have a background in physics, mathematics, statistics, or engineering. A slight majority (57%) of data scientists are well versed in scripting and modeling, while 43% are more skilled in production and engineering.

According to the University of Wisconsin, the median base salary for a data scientist is $130,000, as of 2019. For level 1 scientists with one to three years of experience, they can expect a salary of around $95,000, whereas seasoned professionals and managers can earn anywhere from $146,000 to $257,000.

#data-scientist #data-science #hiring-tips #hiring #recruiting

An Economist’s Value in Data Science

Starting out as a data scientist, I struggled to understand the value economics brings. Now that I understand that data science is far more than knowing how to code, I’ve been able to identify the value that economists such as myself can bring to data science and machine learning. This article is an effort to help economists explain the value they can bring to machine learning roles, as well as help non-economists in data science understand what an economist can bring to the table.

If you’ve ever taken an economics class, you may have heard of economics defined like this:

“the branch of knowledge concerned with the production, consumption, and transfer of wealth.”

If you haven’t, you likely associate economics with labels such as “finance”, “GDP”, and “stock markets”. The field however — and something I love about economics — is far broader than these terms lead on. Economics touches history, geography, business, politics, psychology, marketing, and dozens of other subjects. If you want to dive into the possibilities, check out the Freakonomics podcast. Analysis often includes consideration of the constraints and probabilities surrounding outcomes and effects.

The breadth may lead you to believe that economists think they know everything (and in some cases, you’d be right); that they have a solution to any problem. I’d suggest though that what they really have is a problem-solving framework. The framework includes cost-benefit analysis, cost and output optimization, impact studies, game theory analysis, and — running through each of these — econometrics. Throughout the article, I’ll refer back to a classic data science problem of predicting home prices (a variant of which is also a problem that economists can solve).

My use of the word “economist” refers broadly to individuals who have completed a graduate degree (Masters or Doctorate) in some facet of economics, or who have formally worked as economists. Many of the skills I’ll describe below aren’t sufficiently developed at the undergraduate level (based on my personal experience).

#recruiting #machine-learning #economics #data-science #careers

Please stop giving Take-Home Assignments to Data Science Candidates

Asking candidates to work on Take Home assignments is both unfair and inefficient. Thankfully, alternative methods exist.

Finding the perfect data scientist or analyst for your team is a hard task. You will likely receive hundreds of applications of candidates who all list the same keywords. Screening them is not easy and, to this purpose, (too) many companies assign a take-home data science tasks to some of their top candidates in order to emulate a work situation and evaluate a candidate’s worth.

Candidates are generally sent a data set similar to the ones the company usually works on (or an actual one) and should send back a report or notebook showing how they analysed it and what did they find.

If you are doing this, please stop. 🙏

#data-science #job-search #interview #selection-process #recruiting

5 Simple Job Interview Tips

Disclaimer: this reflects my personal opinions, not those of my employer.

Over the last few years, I have interviewed hundreds of candidates for positions in Software Engineering, Software Engineering Management, Product and Product Marketing Management, Technology Evangelism, and others. It has always bothered me how many people accidentally sabotage themselves, making entirely avoidable mistakes in the early stages of interviews and phone screens, preventing interviewers from getting to know those candidates better, forcing the premature end of the process for them.

I call these mistakes avoidable because not making them is entirely under the interviewee’s control, having nothing to do with aptitude, competence, interviewer having a bad day, or not being fit for a certain position. If you can avoid them (and you can!), then you are already standing out from the crowd, for being able to make your “elevator pitch” in a way that assures interviewers that you’ll be able to handle yourself in a loop with their peers and managers.

Without further ado, this is how you can do better in your job interview:

A short introduction is a short introduction!

Not an invitation for you to read through your resume. So when asked by the interviewer to give “a quick introduction so we can get started”, do just that. Time it to 90 seconds or less. This is about who you are, not (yet) about what you have done. Let’s mock it:

Interviewer: “My name is X, I have been at this company for 5 years, doing X, Y, Z, and prior to this I spent most of my career doing mobile development, now I’m managing this team and am the hiring manager for this position.”

You: “My name is Y, I started in 19xx, when I was born, then went to school, where I learned how to read (…) then I had the opportunity to learn Docker, which I think is the future with Kubernetes, AI, and the Blockchain.”

WRONG. This is what you have done, not who you are.

You: “My name is Y, I’m an Engineer/Marketer/Product person, I’ve graduated from X, been in this market for 5 years, most recently at company Y, and I love being at the intersection of product and engineering, and that’s why I applied for the position”.

Speaking of time

Don’t talk too much, or for too long. If you have been talking for 5-6 minutes without pause, your interviewer is probably already distracted and unable to piece your story together to a coherent whole. Keep answers short and to the point, make pauses, ask if the interviewer has questions, continuously check back to see if the person is still with you. If not, it’s probably time to stop talking.

A couple of extra tips here: if the company interviewing you requires that people take notes about your answers, you can pay attention to when the interviewer has stopped typing. It probably means you are adding nothing to your answer, so change gears. A second cue is that, for video interviews (or live, like in the good ole days), if the person you’re talking to has gone static, not reacting to anything you said, that’s a good sign that you should stop talking.

What’s your motivation?

“Why did you apply for this position?” is considered by many the easiest question in an interview. Well, I have news for you: it isn’t.

There are many ways to answer this question in a way that will immediately raise suspicion in a good interviewer that you don’t know what position you’re applying for, which may be a terminal mistake in a selection process.

Here are some bad answers:

• “Because company X is a great company!” - Yes, it is, but it also might have thousands of job openings, so you’re essentially saying you’d happy to have any of those jobs.
• “Technology is a great sector to be in right now” - A variation on the previous point, it tells nothing about your interest in this position.
• “Because it’s not very hands-on, from the job description” - Even if the position is not hands-on (and those are becoming rare in all sectors), describing your motivation on a negative/lacking/glad-I-don’t-have-to-do-that way sends a bad sign that you are not interested in how things are built, only in the results.

Some good ones:

• “Because the job description says that I would be doing high-impact work with healthcare partners, including leading ones, and that’s something I’m passionate about”
• “I am very passionate about mobile development in Swift and also UX, and looking at your company’s products, I see that you have great care for your user experience, and I’ve been looking for a position where I can excel in both”

#interview #interview-tips #interviewing #job-search #tech-jobs #communication #recruiting #hr

Why Everyone Should Work as a Corporate Recruiter at Some Point in Their Career

Back in college, an advisor suggested that kicking off my career in a sales role would be a great way to gain valuable skills that I’d use throughout my professional life. I feel the same about taking a role as a corporate recruiter.

As a working adult, statistically speaking you’ll be looking for a new job about once every 4 years, which over a 50 year career, adds up to a lot of job searches. So wouldn’t it be beneficial to understand the hiring process from the inside?

I mean, have you ever thought about how recruiters are measured in terms of success from a company standpoint? Or how they interact with hiring managers, and if they read your cover letter? Maybe you didn’t realize that recruiters can easily tell who applied through a big job board versus who sought out the company website directly to apply.

We’re often blind followers of authority, believing that physicians are skilled in the latest procedures, officials always uphold the law and hirers are objective.

However, the common thread is that we’re all human, and as one yourself, you know that people sometimes cut corners, are swayed by emotions and harbor unconscious biases.

If you spend a few years in a corporate recruiting role, here’s what you might see:

Job descriptions don’t align with performance measures. Many hiring managers speculate about the skills they believe will make a candidate successful before writing a job description based on SEO and interesting projects to attract the best candidates, versus spending time building a job description that reflects what an employee will actually be measured on. That’s why many job ads focus more on the company overview and benefits than what they expect a candidate to specifically achieve. You’ll also see similar qualities — team-player, problem-solver, strong communication skills, Bachelor’s Degree — in many descriptions. Yet if you ask why a 4-year degree is a necessary qualification, you probably won’t get a performance-related response. So whether you’re hesitant to apply because the job seems beyond reach or believe you’re a perfect match, be careful not to get too attached to what’s on paper. Instead, do your research, check with your contacts and ask clarifying questions.

**Many jobs are filled before they’re posted. **You’ve likely seen it in your own organization. A hiring manager identifies an internal candidate, but needs to go through the motions of posting the job publicly and interviewing other candidates (who have no shot at landing the role) to adhere to organizational policy. Even if the job is truly available, referrals will get priority before internet applicants, so if you’re going to apply online, it’s worth reaching out to your network to 1) learn if the job is already filled, and 2) get a personal introduction to the recruiter or hiring manager.

**Hiring Managers aren’t trained to hire. **As a recruiter, I’ve lost count of the times I’ve cringed when I’ve heard what an interviewer has asked an applicant. Questions such as “What kind of animal would you be?” are benign (yet have no validity in determining if you’re qualified) as compared to the clearly illegal questions (e.g., “Are you planning to have kids?”). And if you believe that the higher-ups in the organization know how candidates are truly treated (e.g., ghosting, application gymnastics, etc.), it’s unlikely. At the most senior levels, hiring is conducted through referrals, networking and headhunters. Want to better understand what’s happening in the mind of a hiring manager? Click here. Once you realize how bias and emotions impact hiring decisions and the unexpected obstacles you’re likely to face, you can compile a better strategy to clearly demonstrate the value you bring, regardless of who is leading the interview.

#recruiting #interview #careers #hiring #jobs

Building Technical Interviews From Your Team Needs

Asking someone to come and work with you is a big deal. Making the most of a long hiring search can quickly overwhelm a busy hiring manager, recruiter, or a team of interviewers.

Interviews sometimes live as institutional knowledge like a legend passed from colleague to colleague. Others gain mythical predictive powers for telling if a candidate is a “certain type of thinker”. Still, others are just broken but hard to let go of.

I invite you to think about your favorite or least favorite technical interview… and then write it down.

We are going to explore how investing some team whiteboard time and generating some living documents can pay off in making the interview process clear for everyone, and building the team your business really needs.

What does your team need

There are many answers to this question, never just one.

• Competence in a platform or stack
• Something you want to achieve in the next year
• A particular hard-skill or set of soft-skills your current team needs for the next chapter

You may be replacing someone or growing your company. Sometimes that growth is highly deliberate and sometimes you are open to brilliance as it becomes available. (Lucky you)

If you don’t know your needs it’s not worth talking to anyone yet.

In my experience, this is a common failure of management and leadership. It is not something most interviewers can fix without involving others. It’s not something many managers or team leads can fix alone either. Interviewing is a really good example of a team effort.

Flat Earth Genesis GIF By Scorpion Dagger

And, just like that, a meeting was born

**Pen and Paper, Google Docs, Post-Its, whatever it takes **start collecting what your team needs from your new Senior Reactive Stack Assurance Engineer [Level II].

It is not worth investing time in this process until you know what you are looking for. Having money and roadmap objectives larger than your calendar is often not enough.

Everyone here interviewed…right?

Now is the time to iterate from personal experience.

Start reflecting on every aspect of your existing interviewing process across disciplines and collect a set of notes on what kind of interviews you are giving already and how they match up with what you need now.

Everyone that is engaged in interviewing should be able to talk about their own experience. Not only is the empathy and experience critical for conducting a respectful and effective interview, but it’s also key to ensuring you are aligned as a team about what we are doing here as you grow your team.

Don’t have someone like that on your team? You just found something you should write down to add to it. Yay!

Serious Notes

Record the content of your team reflection and strategy meetings in writing.

Brainstorm during your meetings using a collaborative document or stickies on a whiteboard. Have the members of your team think up values, goals, and competencies they think are important.

Brainstorm, discuss, record. Repeat.

Eventually, you should have a role description that properly lists the technologies you use, and the function of the role, and internally have an idea of the subtle needs of the team.

**Review your roadmap. **What is coming up that warrants consideration in the role?

• Are you releasing a new public API?
• Going international?
• Pursuing specific technical or security compliance?

Add anything like that to your list.

What is nice-to-have and what is mandatory?

• Do you need someone that has navigated HIPAA compliance before, or is that just a bonus?
• Is there any reason to talk to anyone that can not consume a local weather forecasting API or doesn’t know what an LRU Cache is?
• Do they need to know what a unit test is?

Have all of this clearly noted in a document that recruiting and your team can find. Many elements of this document will be used in tuning your interview process and helping interviewers ask the right questions.

#business #interview #software-development #recruiting #engineering

Fixing Broken Technical Interviews

Photo by ThisisEngineering RAEng on Unsplash

Hiring a software engineer is hard. It can take months to meet candidates that have the skills and strengths that will grow your team. Convincing them to join is an even heavier lift, often with huge price tags. As interviewers, we often make both challenges harder by chasing after qualities that don’t build strong productive teams.

I want to share what I think a technical assessment interview is supposed to do, and what makes for great technical assessments for businesses of all scales.

Why should you listen to me

I am a seasoned software engineer that has worked in the heart of the San Francisco tech industry building products with startups, and international corporations for over a decade. Primarily bringing apps to peoples iPhones.

I have interviewed with countless companies from FaceFlix giants, to WeWork nomads. I have designed and given technical assessments for the last 5 years, and built candid friendships through out the industry while working with hundreds of brilliant people throughout my career.

Interviewing is a frequent passionate topic of discussion for me - and while it may not be my favorite work activity - I have enough experience to share perspectives I think can improve the interviewing experience and outcomes for those in any industry.

What a technical assessment is supposed to do

Technical assessments first and foremost goal is to evaluate a candidates technical merit. If you yourself have technical merit, this is trivial. You can tell when you are talking to someone that knows your business.

Harder to answer, but more importantly:

What can they add to the team technically? And is it what we need?

Sometimes that means a specific fluency in a technology. Sometimes it is general knowledge of an entire suite or “stack” of technologies and how they work together. Sometimes it is a background in something your team wants to do over the next year or two.

An interview should be designed to answer some reasonably obvious questions. Breaking it down, some of the things I consider when assessing technical ability is:

Code Competency

• Do I believe this person could take the work I see every day and do it to our standards? How confident am I in that?
• Do they understand computer science fundamentals and data structures?
• Do they have experience with the platform/framework/stack we use? How deeply?
• How well do they apply concepts and data structures as tools to approach a problem?

Technical Communication

• How do they get thoughts outside their head? Did we understand each other?
• How did they break down a problem, discuss goals, risks, quality assurance? Will they be productive in technical meetings here?
• How confident am I that code from this person will be what the team considers to be “good code”, and reviewing it will be comfortable and productive?

Teamwork

• How did they respond when I asked them something they didn’t know? How about when I asked for a recommendation, decision, or made a suggestion?
• How on time were we? Did we complete our objective in the allotted time? How easy was it staying on time?
• Was the interview enjoyable? Stressful? Awkward? Did anyone genuinely smile or casually curse?

Level

• In all of the categories how advanced was the performance?
• How well did it meet the needs of the role?
• How much is the team going to succeed or fail by this roles influence compared to my confidence?

I argue that a good technical assessment will leave an interviewer able to speak to these sort of questions if the interview was designed and given well.

Common Anti-Criteria

I have been in a lot of interviews that work against common growth objectives and even feel adversarial at times. While they demystify the recruiting process for interviewers by providing standards to follow, they completely miss out on gaining true understanding of a candidate and using the hiring process to strategize your team growth.

Success (Binary) Measurement

• A task was completed
• The candidate possessed _______ skill or demonstrated ______ ideal

IQ Measurement

• The candidate answered trivia facts correctly and uses idiomatic code
• The candidate solved a riddle, puzzle, algorithm challenge

The Grit Measurement

• The candidate succeeded under stressful conditions
• The candidate did not fall for a trick

These are all interesting things to have happened during an interview, and often would fit into a debrief, however I believe that an interview _should not be designed__to take their measuremen_t.

I often start interviews by explicitly stating that I’m not measuring these things. They are obviously noted, but they aren’t being compared to a standard. This sounds like it would be a big disclaimer but it’s as easy as:

“We want to make progress, but most importantly I want to hear your thought process and get a sense of working together.”

“The project we are going to do is the topic of the interview, but getting to know how you think and work is whats most important here.”

“We want to get to a working solution as quick as we can, but I’m not as worried about how smart you are as how well you can think and learn”

This has a powerful effect of de-escelating the interview and often makes a role more interesting to a candidate having had a comfortable experience that they can mentally map to a daily environment.

The most compelling interviewers I have worked with are able to make candidates forget they are interviewing — Not because of charisma, or co-working chemistry — but because the task that was presented was topical, and the interviewer was engaged not a challenge to be overcome.

#recruiting #interview-tips #software-development #interview #software-engineering #interview-questions

Analyzing Recruiting Data

Last week, I found myself talking to a colleague about the various analytical projects we have been involved over the years. Needless to say, the conversation ventured down a rabbit-hole of complicated statistical analyses, technical terminology and super interesting discoveries. By the end of the conversation, I made sure to bring up one specific analyses I performed a few years ago which uncovered a storyboard of actionable insights and made no mention of statistical significance. No mention of correlation or confusion matrices. No mention of TensorFlow or recurrent neural networks.

Setting the Stage

About two years ago a friend of mine had attended a SuccessFactors conference at which I had presented the power of analytical tools native to the SuccessFactors platform. After the conference he snagged my attention for a few mins and asked if I could potentially help him with a hiring problem he was having. Despite his best efforts, he was having a tough time converting high potential candidates to hires. The problem was a significant roadblock to a short-term corporate strategy as it required a diversification of skill-sets as the company prepared to enter a new product market. I had asked him to send over his data and I would take a look.

Analysis/Results

Upon receiving the data, I decided to dissect the recruiting process into three separate parts; the application, the applicant and the requisition.

The Application

First, I examined the application process by deriving metrics such as “Application Completion Rates”, “Application Drop Off Rates” and “Avg Time to Complete the Application”. To my surprise, the completion rates were above 80%, dropped off rates were minimal and it took on average 3 mins to submit an application. The problem certainly did not reside with the application process.

The Applicant

Next, I turned my attention to the applicant. Which sources were driving the applicant pools? Which sources were producing quality applicants? Having large applicant pools significantly increases the probability of hiring quality candidates. The results of the analyses produced mixed results as the applicant pools were sufficient but highly skewed. Three out of 17 candidate sources were driving 80% of the applicants and most of the quality applicants (ie. candidates which made it to the hiring manager interview stage). These results did not necessarily point me in any direction which might solve the underlying hiring issue but I uncovered potential efficiency and cost-saving factors. These smaller insights are very common in a data mining exercise.

#data-mining #recruiting #io-psychology #metrics #data analysis

What Is Wrong With Data Science Job Interviews?

I. Introduction

Are you a data scientist aspirant? Are you currently applying for data scientist positions? Do you have a data scientist interview coming up? Are you worried about the interview process? If you are currently applying for data scientist jobs, then you should start getting yourself ready for a very long and arduous interview process. After going through a couple of data scientist interview processes, I would like to share my experiences with aspiring data scientists. This article will highlight what to expect in a typical data scientist interview process. In Section II, we describe the interview process. In Section III, we discuss recommendations for improving the interview process. A short summary concludes the article.

II. The Interview Process

Step 1: Initial Contact via LinkedIn from a Recruiter

All the two data scientists interviews that I’ve participated in started with a recruiter contacting me via LinkedIn. The initial message looks like this:

“Hey, Benjamin! I came across your profile on LinkedIn and wanted to reach out to see if you would be open to new opportunities? One of our clients in the Tulsa, OK area that is currently a leader in the web-based monitoring and field automation services for oil and gas is looking for a Data Scientist to join their team! I thought it lined up well with your experience and wanted to make sure I ran it by you! Would there be a good time I could give you a call today to talk more about this role? Thanks and hope to speak with you soon!”

Step 2: Skype Interview with Recruiter

At the Skype interview, the Recruiter asked about my background and what kind of data science projects I’ve worked on in the past. Basically simply trying to figure out if my background and interests line up with the data scientist role being advertised. We also discussed at length about the following:

(i) The data scientist position

(ii) The job location

(iii) Required qualifications

(iv) Job expectations

(v) Work environment

(vi) Approximate pay and benefits

(vii) If I’ll be needing sponsorship for employment

Step 3: Automated Video Interview

It’s now two weeks into the interview process. This time around I was contacted by the director of data science at the company. He asked me to complete an automated video interview. His message read like this:

“Dear Benjamin,Thank you for your interest in a career at eLynx Technologies LLC. We have reviewed your application for Data Scientist — Analytics and we would like to invite you to complete a video interview. You can take the interview at any time with the use of a computer with a webcam. The entire interview will take approximately 10:00 minutes and must be submitted by April 02, 2019.”

Lessons Learned: Here are some tips for automated video interviews:

(i) It’s important you have a broad knowledge about the company and the role you are being considered for. So do your research about the company as you may have to tell them what you know about the company in a nutshell. A good source of information would be the company’s website.

(ii) Be mindful of your background/surroundings (what is in view of the camera) during the interview. Make sure you are in a quiet place that is free from distractions.

(iii) Dress to impress: Always recommended to dress professionally all throughout.

(iv) Keep eye contact with the camera like it’s the eyes of the person you’re interviewing with.

#jobs #interview #data-scientist #data-science #recruiting

Kotlin is not Android.

I have noticed that Android and Kotlin are increasingly becoming synonyms, especially in the minds of IT recruiters.
It’s a very understandable error. They are doing a different job and a good recruiter is not required to know everything that we know, he needs to do his own job well.
But it is wrong.
As you can see on this schema, Kotlin has a larger share of usage in Android than on the JVM. But since the JVM is a bigger platform, the number of Kotlin developers that do Android or something else is roughly similar.

#androiddev #kotlin #recruiting #android-app-development

The Role of Artificial Intelligence in Digital Marketing

Artificial intelligence (AI) is a diverse branch of science, dealing with creating smart machines that can take up tasks which typically require human intelligence. Although we have been exploring AI since the 1950s, it is only in recent years that it has taken root in our daily lives, especially in sales and marketing operations. However, even as 80% of marketing executives predict that AI will revolutionise marketing by 2020, only 23% of businesses have incorporated AI into their processes and offerings today.

The delayed realisation of the potential of Artificial intelligence in digital marketing can cost these businesses their positions in their respective industries. Don’t believe us? Here’s how AI is revolutionising the future of digital marketing.

AI Predicts the Behaviour of Your Customer

Predictive analysis with the help of AI allows you to extract information from data and use it to predict the behaviour and purchase patterns of your customers.

E-commerce giants like Amazon have used this function of AI to effectively target their audiences and also delight them by making their purchase process easier. The ‘Recommendations’ tab that users see while on the website prompts them to buy new products based on their purchase history, while also increasing the sales of the company.

AI Gives Your Customer a Personalised Experience

It is too tedious for most businesses to hire someone to cater to all the queries and complaints of their customers 24*7. And this is where AI-powered chatbots come into play as the unbiased, always available companions of your customers.

Duolingo, the language-based learning program, realised that learning a language requires practising it. Yet, when the app connected people from different countries so that they could chat with each other and improve their language skills, the creators of the app found that people were very hesitant and uncomfortable doing so. So, they introduced their very own bot! You could chat with this bot endlessly in the language you’re learning and have the same experience that you might with a native speaker, without the added stress of embarrassing yourself or troubling someone else. Even though the bots have presently been taken down, the Dulingo spokesperson says that a better version of them is soon to be released.

Artificial Intelligence

AI Helps in Scaling Up Content Marketing

Even though marketers still prefer their content to be written by humans so that it can reach their audiences and connect with them organically, AI can be used to help with the creation until more sophisticated tools are made.

Major brands like Google and Facebook use the AI-powered platform, Acrolinx, to ensure that the different types of content that they create has the same brand voice. Acrollinx understands your guidelines of tone, voice, language, etc. and guides you while you’re writing to make changes to your content so that it suits your requirements.

Welcome 2020 with a New Digital Marketing Strategy

Employing AI in your digital marketing efforts has numerous benefits. With AI being pegged to be the face of increased efficiency, productivity, and profitability, businesses need to do everything in their power to adopt AI or face the risk of being stuck in the past.

Even though this has been said numerous times before, it bears reiterating that AI isn’t here to steal the jobs of humans, but it’s here to revolutionise their true potential. And, for this to happen, professionals should adapt themselves to the changes going around and hop on the AI bandwagon. So, if you need any proof that Artificial intelligence in digital marketing is here to stay, simply try it yourself and enjoy the results!

#jobportal #hiring #vacacny #recruiting