The Risk Data Analyst Job at Pocketly is an excellent opportunity for analytics professionals with 1–3 years of experience who want to work at the intersection of data science, risk analytics, and lending products.
This is a full-time, on-site role in Bangalore, ideal for candidates looking to build a strong career in fintech risk analytics and machine learning–driven decision systems.
📑 Table of Contents
- About Pocketly
- Job Overview
- Key Responsibilities
- Skills and Tools You Will Use
- Eligibility and Qualifications
- Why Join Pocketly
- How to Apply
Risk Data Analyst Job at Pocketly
1️⃣ About Pocketly
Pocketly is a fast-growing fintech lending startup focused on building data-driven lending products using advanced analytics, risk modeling, and AI-powered decision systems.
The company emphasizes:
- Smart credit underwriting
- Risk-first lending strategies
- Technology-driven financial inclusion
2️⃣ Job Overview
Role: Risk and Data Analyst
Company: Pocketly
Location: Bengaluru, Karnataka
Job Type: Full Time
Work Mode: On Site
Experience Required: 1–3 Years
Domain: Data Science and Risk Analytics
This role supports the end-to-end lending lifecycle, including onboarding, underwriting, fraud detection, collections, and upsell strategies.
Risk Data Analyst Job at Pocketly
3️⃣ Key Responsibilities
As a Risk and Data Analyst at Pocketly, you will:
🔹 Lending and Risk Analytics
- Develop and improve analytics-driven strategies for lending products
- Work across the entire customer lifecycle, including:
- Onboarding
- Credit underwriting
- Fraud detection
- Collections
- Upsell journeys
🔹 Data Asset Management
- Create and manage data assets for product and strategy optimization
- Design data processes, controls, and monitoring frameworks
- Enable portfolio-level risk visibility and performance tracking
🔹 Risk Model Monitoring
- Conduct post-implementation validation of risk models
- Monitor and track model performance over time
- Identify drift, risks, and optimization opportunities
🔹 Portfolio Analytics
- Analyze lending portfolios to:
- Identify emerging risk trends
- Mitigate credit risk
- Optimize underwriting strategies
🔹 Machine Learning and AI
- Build and validate ML and AI models to:
- Reject high-risk customers
- Identify low-risk customers for better offers
- Improve decision accuracy and business outcomes
Risk Data Analyst Job at Pocketly
4️⃣ Skills and Tools You Will Use
You will work extensively with:
- Python for analytics and modeling
- SQL for data extraction and analysis
- Microsoft Excel for analysis and reporting
- Risk analytics and lending data
- Machine learning models for credit risk
- Portfolio monitoring and performance metrics
5️⃣ Eligibility and Qualifications
🎓 Education
- Engineering background OR
- Master’s degree in:
- Data Science
- Data Analytics
- Minor degree or diploma in:
- Data Science
- Machine Learning
🧠 Experience
- 1–3 years of experience in:
- Business Analytics
- Risk Analytics
- Data Analytics
- Mandatory experience in a lending company
💡 Technical Requirements
- Minimum 1+ year experience with SQL
- Minimum 1+ year experience with Python
- Strong problem-solving ability
- Excellent communication skills
Risk Data Analyst Job at Pocketly
6️⃣ Why Join Pocketly
- Work in a high-impact fintech environment
- Exposure to end-to-end lending analytics
- Hands-on experience with ML-driven risk models
- Fast learning and career acceleration
- Direct impact on real financial products
- Opportunity to work closely with founders and leadership
Risk Data Analyst Job at Pocketly
7️⃣ How to Apply
📌 Apply via the official job listing
📄 Highlight the following in your resume:
- Lending or fintech analytics experience
- Python and SQL projects
- Risk modeling or portfolio analytics work
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