Job Details

• Define best practice and thought leadership around data science & advanced analytics
• Apply knowledge and expertise in quantitative analysis, predictive /prescriptive modelling and data mining to enhance business operations
• Work with the IT / Technology and Sales & Marketing team, along with the broader Analytics team to deliver cutting edge solutions to solve business problems
• Design, run, and analyse A/B and multivariate hypothesis tests aimed at optimizing customer experience, business KPIs and product funnels
• Analyse experimental data with statistical rigor, ensure accurate interpretation by combining business acumen with detailed data knowledge and statistical expertise
• Drive business decisions using data - turn data into insights and help to surface relevant and personalized content.
• Leverage advanced Big Data Analytics to do consumer analytics, sentiment analysis over a long period of time wrt various dimensions. Big Data platform to analyze customer data from Web, Social and Mobile APP
• Ability to identify variables that could raise risk beforehand and use the variable to create a prediction model for risks
• Provide solutions but not limited to Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization etc.
• Lead and groom the data scientist pool on solving complex problems using data science

• Candidate should have hands on experience in creating at least 2-3 risk models and tested the efficacy of the modeling output.
• Knowledge of Statistics is a must. PHD on data science is an advantage (not mandatory)
• Strong SQL skills, including query optimization, schema design, complex analytics
• Exceptional problem solving and analytical skills
• Knowledge of database modeling and design in a Data warehousing context
• Expert-level proficiency in at least one of R and Python
• Expert-level proficiency and thorough understanding of at least one of the upcoming technologies like deep learning (DL), natural language processing (NLP), reinforcement learning (RL), Bayesian methods etc.
• Expert-level proficiency in statistical / ML predictive techniques such as regression/classification, clustering, dimensionality reduction, forecasting, optimization etc.
• Working experience and statistical clarity in traditional algorithms like linear models, time series models, dimensionality reduction techniques, tree-based learners (Random Forests etc.), kernel based learners (Support Vector Machines etc.), Linear/Dynamic programming, Bagging/Boosting, ensembles etc.
• Working Knowledge and familiarity with the big data stack - Hadoop, hive, spark, map reduce and other big data tools and technologies

Reference ID - GH/CRS/JC//29052018//75701/AGM/ Senior Manager- Head Data Science / Advanced Analytics