Deputy Manager Data Science @ WNS Global Services

Educational Criteria:
Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1 institutions Or
Bachelor of Engineering or MBA from Tier 1 institutions Preferred
Job Description:
The ideal candidate would be adept at understanding customer's business challenges and define appropriate analytics approach to design solution
Should be able to convert mathematical/ statistics-based research/ academic literature into sustainable data science solutions
This is a hands-on role, will be required to manage day to day delivery activities and guide team in executing analytics projects by analyzing large volume of data
Research and bring innovations to develop next generation solutions in core functional areas related to Promotion Effectiveness, Forecasting with detrending methods, Digital Marketing, Customer Relationship Management (CRM), Campaign Management & Data Insights etc.
Provide technical thought leadership, coaching and mentor-ship in the field of data science in working with engineering and other cross functional teams
Evolve the approach for the application of machine learning/deep learning to existing program and project disciplines
He / She would also be responsible for creating Business & technical presentations, reports etc. to present the analysis findings to the end clients and for business development
This role requires excellent communication skills.
Technical Experience: (not all technical exposures are expected from one individual)
Must Have:
Hands on experience in developing models (end to end), esp Marketing Mix Model
Model automation, Bayesian Inference/simulators, Bayesian Filters, GLM (Generalized Linear Models), GMM (Gaussian Mix Models) etc
Recommended system (ALS, MF, Collaborative filtering and Content Filtering), Deep Learning methods
Optimization Method like BFGS, differential evolutionary, MOO (multi objective optimization) etc
Sound understanding of mathematics like probability theory, differential calculus, Laplace and Furrier transformations etc
Tools: Python, SQL, Spark, TensorFlow, big data, Experience on AWS platforms, Knowledge of any visualization tools like Tableau, Quick sight, Qlik sense, Power BI etc. is a plus
Good to Have:
Clustering, Decision Tree, Random Forest, Support Vector Machine, Nave Bayes, GBM, Multiple linear regression, Logistic regression, ARIMA/ARIMAX
Functional/Domain Experience:
Good exposure to Retail, and/or e-commerce domains
Participation/solving Analytics competitions/hackathons will be valued
Relevant Experience: 5+ years of hands on experience in Retail industry
Qualifications
Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1 institutions
Bachelor of Engineering or MBA from Tier 1 institutions Preferred