Business Analyst – Segment Management

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.