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