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Principal Risk Analyst

2 months ago

Gurgaon, Haryana, India Connexions Full time

Job Title: Principal Risk Analyst

Company: Connexions

Location: Remote

Relevant Experience: 3-6 years

Max CTC: 22 LPA

About Us: We are a mission-driven team of finance, analytics, and technology professionals focused on driving financial inclusion to serve the underserved across their credit, savings, and financial needs.

Job Description: The Principal Risk Analyst will be accountable for driving credit policy decisions across the customer life cycle and managing the Lending Portfolio P&L KPIs. This role ensures acceptable risk performance while driving top-line revenue targets by finding expansion opportunities across partner customer segments (banks and telcos).

Key Responsibilities:

Portfolio Strategy & Credit Policy:

Develop credit strategy to drive the GTM strategy, customer eligibility, and limit/exposure decisions using data from telecom, wallet, bureau, and mobile apps.

Optimize customer journey and ongoing communication to drive usage, credit education, and repayment across digital channels (Mobile App, SMS, USSD, OBD).

Collaborate with external debt collection agencies to optimize collection effectiveness and offers.

Build frameworks for measuring periodic performance of existing strategies.

Portfolio Monitoring & Governance:

Develop portfolio tracking metrics and design reports leveraging the tech team.

Monitor PDD MIS and follow up for pending PDDs, ensuring acceptable limits are maintained.

Coordinate with partner teams for due/overdue PDD processes and implement solutions for portfolio health, interfacing with data science, product, and business operations

Skills:

Knowledge of scorecards, credit policies, and risk management in an unsecured context.

Hands-on experience as a data-driven strategy/policy analyst for more than 1 year.

Strong analytical thought process and problem-solving aptitude.

Proficiency in SQL, Python, and Pyspark SQL (Big Data Hadoop/Spark Stack) preferred.

Passion for using data and algorithms to drive underwriting decisions; exposure to ML algorithms is a plus.

Strong entrepreneurial drive and ability to handle ambiguity in a fast-paced environment.