Data Analyst

About the Job

We are looking for a Mid-Level Data Analyst to join Tendo in Manila. You will monitor our largest and highest-risk employer accounts, uncover the insights behind what's happening, and work with Client Success, Product, Sales and Collections to act on them. You will also support prospecting simulations by tracking macro signals and competitor moves, modelling their impact on employers, and recommending what Tendo should do. This is a high-visibility individual contributor role reporting to the Head of Tendo Business.

Responsibilities

• Monitor priority employer accounts: headcount and attrition trends, repayment and delinquency behaviour, out-of-pocket (OOP) patterns, and early-warning signals
• Analyse how attrited customer segments are distributed across large employers and how that mix changes over time
• Assess how well our attrition and OOP scorecards and business rules perform by segment and employer, and propose fixes (new rules, policy changes, inputs to Data Science)
• Turn findings into actions for Client Success, Product and employer stakeholders, and present insights alongside Client Success where needed
• Track macro signals and competitor moves, simulate their impact on current and prospective employers, and recommend actions on pricing, eligibility, limits and targeting
• Build repeatable simulation models and what-if tools for prospecting
• Build Python dashboards (Dash/Plotly with authentication) for employer monitoring, segment analysis and simulations
• Write efficient SQL and Python (BigQuery or similar) and document definitions, assumptions and limitations
• Track the outcome of each recommendation and report results to the Head of Tendo Business

Required Qualifications

• University degree in Data Analytics, Statistics, Mathematics, Economics, Computer Science, Engineering or a related field
• 3+ years (3 to 8 ideal) in data analysis within lending, collections, banking operations, customer analytics or engagement, in B2C or B2B2C companies
• Strong SQL (complex joins, window functions, performance-aware querying)
• Strong Python (pandas, NumPy, visualisation libraries)
• Experience building web dashboards with open-source tools (Dash, Plotly, Streamlit) and comfort with AI-assisted coding, with the discipline to review and test generated code
• Structured problem-solving, from business question to clear recommendation
• Strong communication skills for senior leaders and external employer contacts, with the ability to influence without formal authority

Preferred Qualifications

• BigQuery or another cloud data warehouse (Snowflake, Redshift)
• Experience in payroll-backed, salary-deduction, B2B2C or employer-linked lending, or in attrition and collections analytics
• Scenario analysis, simulation or forecasting, including use of macroeconomic or competitor data
• Understanding of credit scorecards, model-performance metrics (Gini, KS, PSI) and business-rule design
• Account management or client-success analytics experience