Senior Data Scientist (8 to 11 Years)

The team member will be a part of the Artificial Intelligence and Machine Learning, Algorithmic Decision-Making Team (AIML - ADM) and will be working in a fast-paced environment. They will be enabling clients to discover how they can leverage their data using advanced and sophisticated AI/ML algorithms. Data Scientists in the AIML-ADM team should have the capability to work on independent statistical and machine learning research/projects.

Responsibilities

Ability to understand a problem statement and implement analytical solutions & techniques independently with independently/proactively/thought-leadership; Team management and strong stakeholder management skills; Leadership skills to manage a span of Data Scientists; Work with stakeholders throughout the organization to identify opportunities for leveraging company/client data to drive business solutions; Fast learner: ability to learn and pick up a new language/tool/platform quickly; Conceptualize, design, and deliver high-quality solutions and insightful analysis; Conduct research and prototyping innovations; data and requirements gathering; solution scoping and architecture; consulting clients and client facing teams on advanced statistical and machine learning problems; Collaborate and Coordinate with different functional teams (engineering and product development) to implement models and monitor outcomes; Ability to deliver AIML based solutions around a host of domains and problems, with some of them being Customer Segmentation & Targeting, Propensity Modelling, Churn Modelling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modelling Response to Incentives, Marketing Mix Optimization, Price Optimization

Requirements

5.6-11 years in core Data Science & Machine Learning projects; Expert level proficiency in at least one of R and Python; Ability to create efficient solutions to complex problems. Strong skills in data structures and ML algorithms; Experience of working on end-to-end data science pipeline: problem scoping, data gathering, EDA, modelling, insights, visualizations, monitoring and maintenance; Problem-solving: Ability to break the problem into small parts and applying relevant techniques to drive required outcomes; Intermediate to advanced knowledge of machine learning, probability theory, statistics, and algorithms; We use regression, Bayesian methods, tree-based learners, SVM, RF, XGBOOST, time series modelling, dimensionality reduction, SEM, GLM, GLMM, clustering, Deep learning etc. on a regular basis. If you know few of them, you are good to go; B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent

Nice to have

Experience in one of the upcoming technologies like deep learning, NLP, image processing, recommender systems; Experience of working in one or more domains: CPG: pricing and promotion analytics, marketing analytics, trade promotions, supply chain management; BFSI: cross-sell, up-sell, campaign analytics, treasury analytics, fraud detection; Healthcare: medical adherence, medical risk profiling, EHR data, fraud-waste-abuse; Experience in working with Linux computing environment and use of command line tools like sed/awk; Good grasp on databases including RDBMS, NoSQL, MongoDB etc.