Senior BI Analyst

Posted 7 Days Ago
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Taguig, Southern Manila District, National Capital Region, PHL
In-Office
Senior level
Fintech • Payments • Financial Services
The Role
Lead BI and analytics for consumer finance lending products: analyze end-to-end loan lifecycle, monitor lending KPIs, build automated dashboards and real-time monitoring, support risk/collections/fraud analytics, drive portfolio and product performance insights, mentor junior analysts, and translate data into strategic recommendations for stakeholders.
Summary Generated by Built In

Job Title: Senior BI Analyst

Location: BGC, Taguig (Full Time, Onsite)

Job Summary

We are looking for an experienced Senior BI Analyst to lead business intelligence and analytics initiatives across our consumer finance and installment lending business. This role will be responsible for delivering strategic insights, developing advanced reporting solutions, and driving data-driven decision-making across Risk, Credit, Collections, Sales, Product, and Operations.

The ideal candidate has strong experience in fintech, digital lending, or consumer finance, with expertise in portfolio analytics, risk monitoring, collections performance, and business intelligence tools.

Key ResponsibilitiesBusiness & Portfolio Analytics
  • Lead analysis of the end-to-end lending lifecycle, including applications, approvals, disbursements, repayments, and collections.
  • Monitor and optimize key lending KPIs such as Approval Rate, Conversion Rate, PAR, DPD, Roll Rate, Vintage Analysis, and Recovery Rate.
  • Conduct advanced portfolio and customer behavior analysis to identify trends, risks, and growth opportunities.
  • Provide strategic recommendations to improve portfolio quality and business performance.
Dashboard & Reporting
  • Design, develop, and maintain automated dashboards and executive reports using Power BI, Tableau, or similar tools.
  • Build real-time monitoring solutions for Risk, Collections, Fraud, Sales, and Operational performance.
  • Ensure data accuracy, governance, and reporting consistency across business units.
Risk, Collections & Fraud Analytics
  • Partner with Risk and Collections teams to analyze portfolio performance and collection effectiveness.
  • Identify early warning indicators, emerging risks, and delinquency trends.
  • Support credit policy reviews, scorecard validation, and underwriting optimization.
  • Conduct fraud trend analysis and recommend preventive controls and monitoring improvements.
Business Performance & Strategy
  • Analyze product, merchant, and channel performance to identify revenue and growth opportunities.
  • Support pricing, profitability, campaign, and customer acquisition analyses.
  • Develop business cases and data-driven recommendations for strategic initiatives.
Leadership & Stakeholder Management
  • Serve as a key analytics partner for senior management and cross-functional teams.
  • Translate complex data into actionable insights and executive-level presentations.
  • Mentor junior analysts and promote best practices in reporting, automation, and analytics.
  • Lead ad hoc analyses and special projects that support business growth and operational efficiency.
Qualifications
  • Bachelor's Degree in Statistics, Mathematics, Economics, Computer Science, Business Analytics, Finance, or a related field.
  • 5+ years of experience in Business Intelligence, Data Analytics, Risk Analytics, or related functions within fintech, digital lending, BNPL, or consumer finance.
  • Experience from lending or fintech companies such as Home Credit, BillEase, Salmon, Tonik, or similar organizations is highly preferred.
  • Advanced SQL proficiency is required.
  • Strong experience with Power BI, Tableau, Looker, or similar BI platforms.
  • Solid understanding of lending and collections metrics, including DPD, PAR, Roll Rate, Vintage Analysis, and Recovery Metrics.
  • Experience in risk analytics, collections analytics, and fraud analytics.
  • Advanced Excel skills and strong data storytelling capabilities.
  • Experience with Python, R, statistical modeling, or predictive analytics is a strong advantage.
  • Proven ability to manage multiple stakeholders and drive business impact through analytics.

Must have experience from consumer finance or installment lending companies such as:

  • Home Credit
  • Salmon
  • BillEase
  • Tonik
  • or similar lending/fintech organizations.
Preferred Qualifications
  • Experience in digital lending, BNPL, credit cards, or unsecured loan products.
  • Knowledge of data warehousing, ETL processes, and data governance.
  • Exposure to machine learning, forecasting, or predictive analytics.
  • Experience handling large datasets and implementing automated reporting solutions.
Key Competencies
  • Business Intelligence & Advanced Analytics
  • SQL & Data Management
  • Dashboard Development & Automation
  • Credit Risk & Collections Analytics
  • Fraud Analytics & Monitoring
  • Portfolio Performance Management
  • Data Visualization & Storytelling
  • Strategic Thinking & Problem Solving
  • Stakeholder Management
  • Leadership & Mentoring
  • Process Improvement & Automation

Skills Required

  • Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Business Analytics, Finance, or related field
  • 5+ years experience in Business Intelligence, Data Analytics, Risk Analytics, or related functions within fintech, digital lending, BNPL, or consumer finance
  • Prior experience at consumer finance or installment lending companies (e.g., Home Credit, Salmon, BillEase, Tonik) or similar
  • Advanced SQL proficiency
  • Strong experience with Power BI, Tableau, Looker, or similar BI platforms
  • Solid understanding of lending and collections metrics (DPD, PAR, Roll Rate, Vintage Analysis, Recovery Metrics)
  • Experience in risk analytics, collections analytics, and fraud analytics
  • Advanced Excel skills and strong data storytelling and presentation capabilities
  • Proven ability to manage multiple stakeholders and drive business impact through analytics
  • Leadership experience mentoring junior analysts and promoting analytics best practices
  • Experience with Python, R, statistical modeling, or predictive analytics
  • Knowledge of data warehousing, ETL processes, and data governance
  • Exposure to machine learning, forecasting, or predictive analytics
  • Experience handling large datasets and implementing automated reporting solutions
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