KEY RESPONSIBILITIES:
- Use appropriate statistical techniques to develop appropriate analytic solutions for informing customer acquisition and customer retention strategies
- Develop appropriate methodology for analyzing and interpreting results from product features A/B testing
- Work on multiple analytic projects such as user segmentations, user engagement to purchase funnel analysis, user life time value analysis
- Provide data, insights and reporting support to various teams
- Drive the collection of new data and the refinement of existing data sources
- Prepare data for statistical analysis and machine learning algorithms
- Maintain and advance analytic database. Conduct periodic data QA
- Working with technical and non-technical customers to design experiments and communicate statistical results
- Leading training and informational sessions on statistics
- Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business
TO QUALIFY:
- Master’s Degree or PhD in a relevant technical field such as Statistics, Math and Computer Science, Mathematics, Economics and Analytics with 7+ years’ experience in a relevant Data Scientist role post-graduation
- Extensive experience solving business problems using quantitative approaches
- Comfort with extracting, manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- Strong passion for data driven research for answering hard questions with data
- Early adopters of new tools, technologies, etc.
- Decent understanding of business
- Structured problem-solving skills to translate problems into solutions
- Flexible analytic approach that allows for results at varying levels of precision
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Familiarity with relational databases and intermediate+ level knowledge of SQL
- Expert knowledge of R; Experience with other analytic tools such as Looker – a strong plus
- Experience working with large data sets, familiarity/experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, etc.)
- Problem-solving and analytical abilities
- Proficiency in any of the statistical software such as R, S-plus, SAS, STATA, python programming etc.
- Good verbal and written communication skills and an ability to work in a team environment
- A solid grounding in applied statistics including expertise in at least one of the following is a must:
- Reliability models
- Markov Models
- Stochastic models
- Bayesian modeling
- Classification models
- Cluster analysis
- Neural network
- Non-parametric methods
- Time series analysis
- Forecasting
- Multivariate statistics
- Experience in building and deploying business relevant analytics assets
- Experience in real time analytics asset development & deployment
- Experience in Applied Machine learning is an added advantage
- Experience in any of the domains:
- Retail
- Consumer Products Marketing
- Network
- Supply Chain
- F&A
- Procurement
- Life Science
- eCommerce
- Banking Finance
- Health Care
- Human Resources
- Digital Marketing
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