Migo Money Inc is a cloud-based platform that enables companies to offer credit to their consumer and small business customers. Leveraging proprietary datasets, Migo builds ML algorithms to assess credit risk, and then offers credit lines to the companies’ customers. This credit line can be used to make purchases from a merchant or to withdraw cash without the need for point-of-sale hardware or plastic cards. Because of our proprietary data and innovative technical solutions, Migo is able to extend credit to underbanked customers who are not typically covered by credit bureaus.
As a Data Analyst, you will play a key role in driving high-quality decisions across Product, Credit Risk, Finance, and Growth. You’ll own core analyses and reporting, translate complex data into clear business insights, and partner closely with stakeholders to shape strategy and execution. Your work will directly impact approval rates, loss performance, and unit economics across the credit lifecycle.
You will own analyses and reporting that inform credit policy and product experiments, translating complex borrower behavior and risk signals into clear, decision-ready insights. This role is ideal for an analyst who is comfortable working in regulated, high-stakes environments and motivated by using data to responsibly expand access to credit. This role is well-suited for an analyst who is technically strong, business-minded, and motivated by working on problems with demonstrable social impact.
Key Responsibilities
- Lead ad-hoc and exploratory analyses to answer ambiguous business questions and inform product, risk, and growth decisions.
- Design, build, and own high-quality Sigma dashboards for credit performance, funnels, experiments, and partner reporting, with strong standards for accuracy, reliability, and usability.
- Partner with cross-functional stakeholders to define metrics, clarify assumptions, and ensure analyses align with decision-making needs.
- Translate behavioral patterns, experiments, and performance trends into clear, actionable recommendations that improve conversion, repayment, and unit economics.
- Analyze experiments and policy changes, translating results into concrete recommendations around credit policy, underwriting thresholds, pricing, and product design.
- Communicate findings clearly and concisely to both technical and non-technical audiences, highlighting trade-offs, risks, and next steps.
Requirements
- Strong analytical foundation with the ability to clean, transform, and model data from multiple sources.
- Advanced proficiency in SQL; comfort working with complex queries and large datasets.
- Working knowledge of Python or similar analytical tools for deeper analysis is preferred.
- Experience with at least one BI tool (e.g., Sigma, Tableau, Power BI); Sigma experience strongly preferred.
- Excellent communication skills, with the ability to frame problems, articulate assumptions, and tell a compelling data story.
- High attention to detail and a strong sense of ownership over data accuracy and integrity.
Experience
- 3–5 years of professional experience in analytics, data science, or a related role.
- Hands-on experience analyzing credit, lending, payments, or financial-risk data.
- Demonstrated ownership of end-to-end analyses that informed policy or product decisions.
- Experience supporting experiments, cohort analysis, or longitudinal performance tracking.
- Prior experience working cross-functionally with Risk, Product, Marketing, Finance, Operations, or Compliance teams.
Method of Application
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