Congratulations to Vigneshwaran Dharmarajan on his new job!
Congratulations Vignesh! Vigneshwaran just received a job offer as a data scientist and has relocated to Kansas. Vignesh recently completed his Master’s of Science in Data Science and Analytics in the Gallogly College of Engineering at the University of Oklahoma and he also worked for me as a TA in the Fall of 2017 for the ISE/DSA 5103 Intelligent Data Analytics course.
Vignesh came by to see me the other day to let me know about his recent success and then sent me a note describing a little bit about the interview process and how his education in the DSA program helped him land the job.
I would like to thank you so much for offering the Intelligent Data Analytics (IDA) course. The knowledge that I acquired through the course work helped me get job offer as Data Scientist. As part of the interview process, I got a case study where I was given a real world data set to analyze, predict and to present the results that decisions can be made from. From the course work, I have learnt techniques like exploratory data analysis, feature engineering, train model, validate the model & future prediction. With this I can be able to perform all the requirements given in the case study without any difficulty and used all types of visual aids learnt in the course work to present the data more palatable or comprehensible. This helped me moved to the next round and in the final round the discussion started with the learning & the projects did in the IDA course along with other experiences & projects. I know, the knowledge and techniques I learnt in the course is a significant factor for getting this job offer and will definitely help me to apply this in the industry to improve the business process. Thank you once again!
— Vigneshwaran Dharmarajan
I have heard similar stories lately regarding what companies seem to care about in hiring new data scientists. They regularly require candidates to address case studies and data sets as a first step in the interview process. I am glad that the DSA program helped prepare Vignesh for this.
Vignesh also supplied me with the job description (excerpted below with highlights added).
Job Description
Provide accurate and timely data support, analysis and maintenance using statistical math and algorithms on a variety of reports, charts, models and projects that have a direct impact on all aspects of the organization.
Build Efficiency
- Work closely with the Lead Data Scientist regarding efficiency, analysis, quality goals, and market and product trends
- Contribute using SQL and R language to the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
- Support cross-functional teams on the day-to-day delivery of projects and initiatives
- Find, clean and integrate data into usable and helpful information
- Identify and utilize data analysis and measurements effectively to identify performance trends, shortfalls
- Identify campaigns, strategies, and processes that drive highest results
- Turn data into insight: segment, cluster, model and mine to better understand behaviors and trends
- Analyze why things happened and predict what could happen in the future based on data
Maintain Operational Standards
- Identify gaps in current data systems, drive and contribute to development of systems to bridge gap
- Plan and execute ongoing strategies including maximization of technologies and processes
- Take initiative to make things better and provide solutions for challenges
Developing People
- Model Customer Service principles and practices and foster an environment where those principles guide accomplishing goals and interacting with internal and external Customers
- Anticipate operational needs based on volume/expansion and make recommendations
- Drive change – produce clear, understandable visualizations and reports to share with Senior Management. Partner with management to design tests and implement your finding
As a quick note: in the ISE/DSA 5103 course you will learn and use R, learn how to clean and deal with messy data, work very hard on turning data into insight, use visualizations to explore and explain data, and learn an array of techniques for predictive modeling, among other things.
I will post more student’s stories on data science interviews and jobs in the future. And if you are a former student who wants to be highlighted in the blog, just send me your information and picture and I am happy to boast about your success!