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.