Team Lead - Data Science

About DMI:

Led by technology, powered by creative thinking and driven by innovative partnerships, DMI is reimagining the transmission of credit in India.

Founded in 2008 by Shivashish Chatterjee and Yuvraja C. Singh, and supported by a deeply experienced team, DMI has grown into a pan-India credit platform with core businesses in corporate lending, housing finance, digital consumer and MSME finance and asset management.

Qualifications

• Minimum Qualification required: Masters in Economics, BA or Technology
• Qualifications preferred:

Work Experience

• Minimum 7-10 years of experience
• Experience in Analytics as well as BFSI credit domain, exposure to programming
• Team management skills, communication skills, project management skill

Relevant Experience (In years/months): ~ 3-4 years in Model Development, BFSI domain expertise, Machine Learning. Products are Personal Loan, Consumer Loan, Business Loan.

Job Description

Contributing to the company’s profitability through business decision making depending on the effectiveness of the data driven results generated through models developed & maintained by the team

1. Functional leadership

• Structuring solutions to business problems, helping team execute the same
• Ensuring efficacy and appropriateness of the solution provided by the team
• Ensuring efficient programming and automation
• Driving the projects by application of both data analytics as well as BFSI credit domain knowledge
• Mentoring & thought leadership to improve team productivity

2. Model Development

• Laying down specific approach for developing model basis statistical analysis of data for a partner
• Guiding the team through validation of the model basis accuracy figures and model performance on test data
• Suggesting alternate approaches to improve model performance

3. Model Deployment

• Interacting with internal teams to communicate integration needs
• Deciding on when to deploy a model
• Positioning the usage of deployed model within the integration process with that partner

4. Effective communication and collaboration

• Arranging knowledge sharing sessions within the team by identifying critical topics
• Discussing with senior management on the results and improvements as well as on further projects to be taken up by the team
• Liaising with other teams to ensure smooth integration of our workflow with rest of the business

5. Analysis & recommendations for business

• Identifying gaps and opportunities
• Presenting data driven results to senior management and business
• Formulating recommendations for business basis analysis of data done by us

6. Model monitoring

• Working with the team on monitoring the model performance post deployment
• Deciding on recalibration of the model in case model results are not satisfactory on the actual data
• Designing approach to showcase loss trends and model performance

7. Project identification and prioritization

• Identifying projects for the team through discussions within team as well as with senior management and cross team stakeholders
• Prioritizing projects and tasks, assigning them to the team basis current resource utilization
• Guiding each team member throughout the project/ task being taken up by him/her