Manager - Risk Analyst - Internet/eCommerce - IIT/NIT/BITS

Job Description:-

Data generation and storage:

- Ongoing generation of data tags / variables based on implicit and explicit data, depicting customer purchase, risk and behavioral properties

- Maintain quality of the variables, and fill rates; Devise methods to improve data collection

Data strategies:

Data science:

- Create new variables. Imbibe the value of creating and testing various strategies across the spectrum to learn and implement data based solutions

Product:

- Create customer events, establish customer identity, analyse customer product usage behavior and engagement, suggest areas of improvement in customer engagement

Marketing:

- Establish customer funnels across channels, evaluate cost effectiveness of sub-channels and how to use data to shape acquisition while marrying sub-channel performance with customer NPV (risk and return)

Collections and operations:

- Create data based strategies to bring efficiency in collections and operations

Risk policy and underwriting:

- Creates value by monitoring performance of existing risk policy, testing new policy, bringing new variables and models and improving acquisition performance

- Manage approval rates across channels while managing risk performance

- Pro-active portfolio management to prevent delinquency through franchise management by line, portfolio offer management

- Manual evaluation and tracking of individual applications to incorporate learnings in risk policy

- Assessing different data vendors to understand various capabilities that can be used for customer assessment

- Support business by designing relevant challenger programs to test new segments and monitor its performance

- Model customer attrition, spend, revolve, month-end balances, in-voluntary attrition(risk) and bring together assumptions to make customer NPV based decisions

Policy implementation:

- Responsible for ensuring the policy rules automated in system are working as required

Fraud management:

- Responsible for minimizing fraud risks by constantly evaluating process gaps and improvising fraud check policy

Monitoring and reporting:

- Meticulous about reporting weekly / biweekly / monthly performance, and while adding value through deep process knowledge through insights on each metric movement

- Automates reports where high frequency reporting and monitoring is required

- Create metrics to evaluate performance of the solutions created

Preferred Qualifications

- Bachelor's degree from Tier-1 college: IIT, BITS, NIT

- 2-3 years of experience doing quantitative analysis

- 2-3 years of experience building statistical models, feature engineering, sparse data models

- Understanding of statistical analysis, experience with R, Python, SQL, SAS, SPSS, Visualization tools (Tableau/Domo/Power BI), etc.

- At least 6 months - 1 year of experience guiding/managing work of juniors

- Experience around credit risk & understanding of related data (bureau variables, etc.)

- Experience in initiating and driving projects to completion with minimal guidance