DATA ANALYST | Predictive Analytics Decision Management

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 Originally posted on Himalayas