Business Analyst

Role Summary The Business Analyst – Segment Management is responsible for designing, analyzing, and continuously optimizing customer segments across the lending lifecycle . This role sits at the intersection of business strategy, advanced analytics, and execution , acting as a strategic partner to Product, Risk, Marketing, Operations, and Finance teams.
The role requires a hybrid BI + BA profile : deep hands-on data analytics capability combined with strong business logic, financial acumen, and structured problem-solving skills. The individual will translate complex data into actionable segment strategies that drive portfolio growth, profitability, risk balance, and customer experience .

Key Responsibilities
1. Segment Strategy & Design
Design and maintain customer segmentation frameworks across the end-to-end lending lifecycle, including:
Acquisition segments (new-to-credit, new-to-platform, repeat borrowers)
Risk segments (score bands, behavior-based cohorts, early-warning segments)
Value segments (LTV-based, profitability-based, pricing sensitivity)
Behavioral segments (repayment behavior, utilization patterns, engagement)
Define clear segment objectives , eligibility rules, and success metrics aligned with business strategy.
Continuously refine segment definitions based on performance data and evolving portfolio dynamics.

2. Advanced Analytics & BI Ownership
Perform deep-dive analyses on segment-level performance , including:
Approval rate, conversion rate, booking volume
Utilization, repayment behavior, delinquency, roll-rates
Loss rate, margin, contribution profit, LTV
Own and enhance segment-level dashboards and reporting (e.g., Tableau, Power BI, Looker, Grafana).
Build self-serve analytical datasets and metric definitions to ensure consistency across teams.
Ensure data accuracy, reconciliation, and alignment with Finance, Risk, and Data teams.

3. Business Problem Solving & Diagnosis
Act as a first-line analytical problem solver for segment-related business issues, such as:
Sudden drop in approval or conversion within a segment
Unexpected deterioration in repayment or delinquency
Misalignment between growth and risk performance
Conduct root-cause analysis using structured frameworks and data triangulation.
Translate analytical findings into clear, actionable recommendations for stakeholders.

4. Cross-Functional Collaboration
Work closely with:
Product teams to design segment-specific journeys, pricing, and offers
Risk teams on score thresholds, policy tuning, and early-warning indicators
Marketing / Growth teams on targeting, campaign optimization, and personalization
Operations & Customer Support on segment-specific issues, complaints, and exceptions
Finance on profitability, reconciliation, and forecasting
Serve as a bridge between business stakeholders and data/engineering teams , ensuring analytical requirements are correctly translated into data solutions.

5. Experimentation & Optimization
Support segment-level experimentation (A/B testing, policy experiments, offer testing).
Define hypotheses, success metrics, and measurement frameworks.
Analyze experiment outcomes and provide data-driven recommendations for rollout or iteration.

6. Executive & Management Reporting
Prepare clear, concise, and insight-driven presentations for senior management.
Convert complex data into structured narratives highlighting risks, opportunities, and trade-offs.
Support strategic discussions around portfolio mix, growth targets, and risk appetite at a segment level.

Required Qualifications & Experience
Education
Bachelor’s degree in Business, Finance, Economics, Statistics, Data Science, Engineering, or related fields.
Master’s degree (MBA, Analytics, Finance) is a strong plus.

Experience
5–8+ years of experience in:
Business analytics, BI, segment management, or strategy roles
Lending, credit, banking, or fintech environments
Proven experience working in large financial institutions or scaled fintech platforms .
Direct exposure to retail lending products (personal loans, BNPL, credit cards, installment loans).

Technical & Analytical Skills
Strong hands-on capability in:
SQL (advanced querying, joins, window functions)
BI tools (Tableau, Power BI, Looker, etc.)
Excel / Google Sheets (advanced modeling, scenario analysis)
Solid understanding of:
Credit metrics and portfolio KPIs
Segment-level profitability and unit economics
Experience working with large, complex datasets across multiple systems.