Job Description

• Build predictive models for credit risk, collections, fraud, and other business needs in Financial Industry

• Manage and own the entire end-to-end lifecycle of building and validating predictive models along with their deployment and maintenance

• Engineer predictive features from existing data to build refined customer profiles

• Identify external data assets to bring into the model mix Work backwards to conceptualize and design analytic model frameworks to solve business problems

• Strong communication skills to share your learnings, lead with the given strategy, get multiple stakeholders to buy into the vision and execution of the analytics roadmap

Requirements

• Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)

• At least 4 years of hands-on experience in building, evaluating, and monitoring ML collection risk or consumer credit scoring models for financial products

• At least 2 years of leadership experience Solid understanding of mathematics and statistics

• Sound knowledge of machine learning concepts such as Bagging, Boosting, Recommendation Engines, etc Expert in feature creation on a variety of data types

• Professional experience in building machine learning analytics model development

• Understanding of trade-offs between model performance and business needs

• Proven experience to formulate data science solutions to business problems

• Proven ability to communicate with business and know business needs

• Work experience and knowledge of more than one domain is a plus - Risk Analytics, Marketing Analytics, Fraud analytics etc.