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.
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!”
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
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
For this week’s latest data science job openings, we have come up with a curated list of job openings for data scientists and analysts from last week.
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With the world starting to open amidst the COVID-19 pandemic, the number of jobs available in data science sees an upward trend in India as we inch closer to providing vaccines for everyone.
The number of vacancies for data science jobs on the top job portals in India increased by 53% from when India eased the lockdown restrictions on June 8 to Nov 30, according to the data collated by AIMResearch. Although it is difficult to ascertain the exact number of open jobs, the top job portals in India, Naukri, LinkedIn, and MonsterIndia together showed almost 125,000 vacancies on Nov 30.
However, the pandemic did result in a decrease in the number of open data science jobs at the start as vacancies reduced from 101,562 from Dec 17 last year to 81,704 on June 8. Despite this decrease, India’s share of open data science jobs in the world increased from 7.2% in January to 9.8% in August.
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For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.
“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.
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The buzz around data science has sent many youngsters and professionals on an upskill/reskilling spree. Prof. Raghunathan Rengasamy, the acting head of Robert Bosch Centre for Data Science and AI, IIT Madras, believes data science knowledge will soon become a necessity.
IIT Madras has been one of India’s prestigious universities offering numerous courses in data science, machine learning, and artificial intelligence in partnership with many edtech startups. For this week’s data science career interview, Analytics India Magazine spoke to Prof. Rengasamy to understand his views on the data science education market.
With more than 15 years of experience, Prof. Rengasamy is currently heading RBCDSAI-IIT Madras and teaching at the department of chemical engineering. He has co-authored a series of review articles on condition monitoring and fault detection and diagnosis. He has also been the recipient of the Young Engineer Award for the year 2000 by the Indian National Academy of Engineering (INAE) for outstanding engineers under the age of 32.
Of late, Rengaswamy has been working on engineering applications of artificial intelligence and computational microfluidics. His research work has also led to the formation of a startup, SysEng LLC, in the US, funded through an NSF STTR grant.
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Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
In this article, we list down 50 latest job openings in data science that opened just last week.
(The jobs are sorted according to the years of experience r
Skills Required: Real-time anomaly detection solutions, NLP, text analytics, log analysis, cloud migration, AI planning, etc.
Skills Required: Data mining experience in Python, R, H2O and/or SAS, cross-functional, highly complex data science projects, SQL or SQL-like tools, among others.
Skills Required: Data modelling, database architecture, database design, database programming such as SQL, Python, etc., forecasting algorithms, cloud platforms, designing and developing ETL and ELT processes, etc.
Skills Required: SQL and querying relational databases, statistical programming language (SAS, R, Python), data visualisation tool (Tableau, Qlikview), project management, etc.
**Location: **Bibinagar, Telangana
Skills Required: Data science frameworks Jupyter notebook, AWS Sagemaker, querying databases and using statistical computer languages: R, Python, SLQ, statistical and data mining techniques, distributed data/computing tools such as Map/Reduce, Flume, Drill, Hadoop, Hive, Spark, Gurobi, MySQL, among others.
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