Senior Data Scientist

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 clients 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.