Decision Analytics Lead

Role Overview

This role sits at the heart of how decisions get made at d.light, connecting the teams that build our data infrastructure with the teams that act on data every day. You will take the most ambiguous and high-stakes business questions — the ones a standard report can't resolve — and turn them into clear, defensible recommendations that leaders and operational teams actually use. Your success is measured not by model complexity but by whether better decisions happen because of your work.

Key Responsibilities

• Own complex business questions from start to finish: clarify vague requests from leadership, identify what data is needed, deliver a rigorous answer, and ensure it leads to a concrete decision.
• Develop forecasts and predictive models that are accurate enough to guide planning, while keeping the logic transparent so stakeholders can trust and explain the results.
• Create risk scores, customer segments, and prioritised action lists that field teams can apply directly in credit, commercial, and collections work.
• Design and evaluate experiments for business interventions, including setting up test and control groups, then report honestly on what changed and what did not.
• Work across the modern data stack hands-on — writing SQL and dbt models in Redshift, building analyses in Python or Jupyter, and using Tableau when a visual is the clearest way to make a point.
• Spend time embedded with commercial, credit, supply chain, finance, and country teams — including in the field — so your analysis reflects how the business actually operates.
• Translate complex analytical output into simple, actionable recommendations for non-technical audiences up to senior leadership, acknowledging assumptions and uncertainty without letting them block progress.
• Make your work reusable: partner with the Data Platform team to turn your best datasets, metrics, and definitions into shared warehouse models, and hand recurring outputs to Analytics Delivery.

Requirements & Qualifications

• At least 5 years of experience answering complex analytical questions in an operational business, or equivalent depth demonstrated through a strong track record of analysis that changed decisions.
• A business-first mindset — equally comfortable in a commercial or credit review as in a notebook, preferring to answer a real operational question well over building an elegant model nobody uses.
• Strong SQL skills and the ability to build your own data models against a cloud data warehouse; experience with Redshift and dbt is a plus.
• Strong Python and Jupyter skills for analysis, automation, and modelling, with the discipline to write code that others can follow.
• Working knowledge of applied statistics and pragmatic exposure to regression, classification, forecasting, and clustering — you know when a simple, well-built analysis beats a complex model.
• Ability to scope an ambiguous question into a concrete plan: define what would answer it, what data exists, what is good enough, and when to stop.
• Comfort with imperfect operational data — you investigate outliers and data quality issues rather than modelling around them.
• Excellent communication and documentation skills, including explaining method, assumptions, and uncertainty to non-technical audiences; familiarity with Tableau or similar tools is expected.
• Exposure to consumer credit, PAYGo, lending, distribution, or supply chain is a strong plus, as is experience where analysis had to survive contact with an operational team.
• A genuine passion for d.light's mission and the customers we serve, plus comfort in a startup-like environment where structure is still being built and you are expected to help build it.

What We Offer / Why Join

This is a chance to do analysis that directly shapes company strategy and operational practice, with visibility at the highest levels of the organisation. You will work alongside a dedicated BI team, have room to grow your statistical and modelling skills, and see your work implemented in live business systems rather than left in presentations. The role comes with a competitive remuneration package, medical cover, and a pension.