Job Title: Product Data ScientistKey Skills: Python or R, SQL, DataExperience: 6+ yearsLocation Hermosillo or Mexico CityMode: OnsiteWe at Coforge are hiring Position ******-PE-MX-TM2-6) with the following skill set.This role sits at the intersection of product analytics, experimentation, and data science — embedded directly with Product Management to help shape and grow our Home Improvement lending product.
You'll be the analytical backbone for a product team making high-stakes decisions about underwriting funnels, borrower experience, and growth, translating messy data into clear evidence and, where it counts, into models and instrumentation that ship.
It's a high-impact role for someone who is equally comfortable running a rigorous A/B test, writing a dbt model, and explaining a lift curve to a VP.ResponsibilitiesPartner day-to-day with Home Improvement Product Managers as their embedded data science and analytics resource — turning open-ended product questions into structured analyses and clear recommendationsDesign, run, and interpret experiments (A/B and quasi-experimental) across the borrower funnel — from offer presentment through origination — with rigor around power, sample ratio mismatch, novelty effects, and interaction risk across concurrent testsDefine and own the metrics framework for the Home Improvement product line: north-star and guardrail metrics, funnel and cohort definitions, and the instrumentation needed to measure them reliablyWork with engineering to ensure event tracking and logging are complete, accurate, and well-documented at the point of instrumentation, not discovered as gaps after the factBuild and maintain data pipelines and models (e.g., SQL/dbt transformations, feature pipelines) well enough to be self-sufficient for most analyses and to collaborate credibly with data engineering on the restDevelop and validate statistical and ML models supporting product decisions — response/propensity models, funnel drop-off and conversion models,



segmentation, and early-stage risk or pricing signals in partnership with credit strategy — with attention to fairness, explainability, and regulatory context appropriate to a lending businessBring AI fluency to the work: use LLM- and agentic-tooling to accelerate exploratory analysis, requirements gathering, and documentation, while knowing where automated outputs need human judgment and validation before they inform a decisionCommunicate findings in a way that drives action — clear write-ups, well-chosen visualizations, and recommendations tied to specific product or roadmap decisions, not just descriptive dashboardsContribute to PI planning and roadmap discussions by sizing opportunities, flagging measurement risk in proposed initiatives, and helping the team commit to work that can actually be evaluatedContinuously monitor product and experiment performance post-launch, and proactively surface anomalies, regressions, or new opportunities rather than waiting to be askedRequired Qualifications5+ years of experience in a hybrid analytics/data science role (e.g., analytics consulting, product data science, applied statistics) with a track record of directly informing product decisions; bachelor's degree or higher in a quantitative field, or equivalent combination of education and experienceYou have strong grounding in statistics and experimentation — hypothesis testing, causal inference, experiment design,



and you can explain the difference between a significant result and a meaningful oneYou're fluent in SQL and at least one scripting/statistical language (Python or R), and you're comfortable enough with data engineering fundamentals (pipelines, transformations, data modeling) to build what you need and partner effectively with engineers on the restYou can develop, validate, and communicate the tradeoffs of statistical and machine learning models, and you know when a simpler model or a well-designed experiment beats a complex oneYou use AI tools in your day-to-day work — for exploratory analysis, documentation, and accelerating routine analytics — and you know when their outputs need scrutiny before they touch a product decisionYou think like a consultant: you get to the real question behind the question, structure ambiguous problems, and land on recommendations stakeholders can act onYou have good judgment about rigor versus speed, and you don't cut corners on measurement integrity just to hit a deadlineYou're a clear communicator who can flex between a technical conversation with engineering and a decision-focused conversation with product and business stakeholdersYou're curious about how data, experimentation, and AI can change what's possible in consumer lending products, and you're always looking for a better way to answer the questionNice to haveBackground in fintech, consumer lending, or home improvement/contractor financingExperience with CDP platforms, event instrumentation tooling (e.g., Segment, mParticle, Amplitude), or experimentation platformsHands-on experience with credit or risk modeling, pricing strategy, or marketing decisioningExperience with dbt, Airflow, or similar data pipeline/orchestration toolsPrior experience embedded directly with product teams in an agile/scrum environment Posted On: September 8, ****At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

📌 Product Data Scientist (México)
🏢 Encora
📍 México