An ML Engineer builds artificial intelligence (AI) systems that leverage huge data sets to generate and develop algorithms capable of learning and eventually making predictions. Each time the software performs an operation, it “learns” from those results to carry out future operations more accurately.

Ability to understand a problem statement and implement analytical solutions techniques independently with independently / proactively / thought-leadership.
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