Job Descriptions

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

ii. Manage and own the entire end-to-end lifecycle of buildings and validate predictive models along with their deployment and maintenance

iii. Engineer predictive features from existing data to build refined customer profiles. Identify external data assets to bring into the model mix

iv. Work backwards to conceptualize and design analytic model frameworks to solve business problems

v. 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

c. Requirements

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

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

iii. At least 2 years of leadership experience

iv. Solid understanding of mathematics and statistics

v. Sound knowledge of machine learning concepts such as Bagging, Boosting, Recommendation Engines, etc

vi. Expert in feature creation on a variety of data types

vii. Professional experience in building machine learning analytics model development

viii. Understanding of trade-offs between model performance and business needs

ix. Proven experience to formulate data science solutions to business problems

x. Proven ability to communicate with business and know business needs

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