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S #2532
Applications open Full-Time Job

Business Analyst - Assistant Manager - Lending Reserve

Paytm

  • Noida, India
  • Not disclosed
  • 2–5 Years
  • Posted Yesterday
HR
Recruiter contact
Recruiter / hiring contact
No public email in this post. Use a source-linked contact instead.

About the role

About Us

Paytm is India's leading financial services company that offers full-stack payments & financial solutions to consumers, offline merchants, and online platforms. The company is on a mission to bring half a billion Indians into the mainstream economy through payments, commerce, banking, investments, and financial services. One97 Communications Limited, which owns the Paytm brand, was founded by Vijay Shekhar Sharma.

About the team

Our lending analytics team owns the personal loan funnel end-to-end — from lead generation through disbursal —working across risk, product, growth, and call center operations to continuously improve conversion, approval rates, and disbursal volume across multiple lending partners.

What you'll do

  • Own and monitor the personal loan funnel across multiple lending partners, tracking conversion, drop-off, and approval rates at each stage (lead, application, underwriting, disbursal)
  • Conduct cohort-level performance analysis to identify underperforming lender segments or funnel stages, and work with the risk team to refine approval logic
  • Design and maintain real-time dashboards (Looker) for cross-functional stakeholders across Business, Product, Growth, and Risk Tech teams
  • Build and maintain threshold-based alerting systems to flag funnel deviations and anomalies, enabling proactive response
  • Partner with the call center/operations team to design data-driven prioritization models that improve outreach efficiency and conversion
  • Analyze drop-off and retargeting opportunities to recover users lost at various funnel stages
  • Respond to ad-hoc data requests from finance, growth, and call center teams (disbursal reporting, trend diagnostics, etc.)
  • Identify opportunities to automate recurring reporting and manual workflows, including using AI tools, to improve team efficiency

What we're looking for

  • 2–5 years of experience as a Business Analyst / Data Analyst, ideally in fintech, lending, or a related consumer- tech domain
  • Strong SQL skills; working knowledge of Python for basic data analysis is a plus
  • Hands-on experience with BI/dashboarding tools (Looker, Power BI, or similar)
  • Solid grasp of statistics and ability to translate data into clear, actionable business narratives
  • Experience working with or analyzing lending/credit/BNPL funnels is a strong plus
  • Comfort working cross-functionally with risk, product, growth, and operations teams
  • Bonus: experience using AI tools (e.g., Claude, ChatGPT) to automate reporting or analytical workflows
  • Google Apps Script and Spark experience is a plus

Nice to have

  • Experience negotiating or influencing external partner (e.g., lender/financier) risk criteria using data
  • Exposure to call center/ops prioritization or resource-allocation modeling

Join Us

A collaborative, output-driven environment that brings cohesiveness across businesses through technology.

Opportunities to improve Average Revenue Per User (ARPU) by unlocking massive cross-sell opportunities across Paytm’s user base.

A solid 360 circle feedback culture supported by peer teams aligned with your goals.

Compensation

If you are the right fit, we believe in creating wealth for you With enviable 500 mn+ registered users, 21 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants – and we are committed to it. India’s largest digital lending story is brewing here. It’s your opportunity to be a part of the story!

Eligibility & process

Who can apply

• 2–5 years of experience as a Business Analyst / Data Analyst, ideally in fintech, lending, or a related consumer- tech domain • Strong SQL skills; working knowledge of Python for basic data analysis is a plus • Hands-on experience with BI/dashboarding tools (Looker, Power BI, or similar) • Solid grasp of statistics and ability to translate data into clear, actionable business narratives • Experience working with or analyzing lending/credit/BNPL funnels is a strong plus • Comfort working cross-functionally with risk, product, growth, and operations teams

Skills & stack

Python SQL Power BI Apache Spark Business Analysis Advanced Excel Agile/Scrum JIRA

Selection process

  1. As described in the employer's job posting.

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, SQL, Power BI, Apache Spark, Business Analysis, Advanced Excel, Agile/Scrum, JIRA) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Paytm Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Paytm as a Business Analyst - Assistant Manager - Lending Reserve?
Highlight Paytm's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Paytm Not disclosed
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