Decision Analytics Lead

About the Team and Role

The Business Intelligence (BI) group at d.light manages the entire data and analytics infrastructure—from raw data ingestion and processing to delivering dashboards, automations, and decision-making tools that drive strategic initiatives across the company. The team is divided into two main segments: Data Platform, which handles the warehouse, pipelines, and AI infrastructure, and Analytics Delivery, which collaborates with departments to develop business-critical insights.

The Decision Analytics Lead bridges these two segments, addressing complex and strategic business queries that dashboards alone cannot solve. These questions span credit and collections, commercial operations, supply chain, and finance. Success in this role is measured by the impact of decisions supported, rather than the complexity of models used.

Key Responsibilities

• Take ownership of challenging, ambiguous questions from leadership and departments, refining them into clear, answerable problems and guiding them to actionable decisions.
• Develop forecasts and predictive modeling tools that are both reliable for planning and transparent to build trust.
• Create scoring systems, customer segmentations, and prioritized action lists to enable operational teams to act effectively.
• Design and analyze experiments with control groups to objectively evaluate the effectiveness of interventions.
• Utilize a broad modern data stack, including SQL, dbt, Python, Jupyter notebooks, and Tableau, to access data and build models tailored to the question at hand.
• Engage deeply with commercial, credit, supply chain, finance, and regional teams, including field visits, to ensure analyses are grounded in operational realities.
• Communicate complex technical findings into straightforward recommendations for non-technical stakeholders and senior leadership, being transparent about assumptions and uncertainties.
• Create reusable analytical assets by collaborating with Data Platform and Analytics Delivery teams to incorporate datasets, metrics, and definitions into company-wide models and tools.

Success Indicators

• Clearing backlogs of unanswered business questions with well-documented, credible answers.
• Effecting tangible changes in decision-making by department heads and leaders through impactful analyses.
• Delivering operational tools such as scores and forecasts that are actively used rather than passive presentations.
• Developing new metrics and datasets that become part of enterprise data assets, accessible and shared with others.
• Establishing a reputation among business teams as a go-to expert for complex, unstructured analytical challenges with well-documented, reproducible work.

Candidate Qualifications

• A business-oriented analyst focused on solving real-world operational questions rather than building models for their own sake.
• Minimum five years of proven experience answering complex analytical questions within an operational business setting or equivalently demonstrated capabilities.
• Proficiency with SQL and experience constructing data models independently within cloud warehouses, preferably with Redshift and dbt.
• Strong skills in Python and Jupyter notebooks for analysis, automation, and modeling, producing well-documented, maintainable code.
• Familiarity with applied statistics and pragmatic use of machine learning methods such as regression, classification, forecasting, and clustering, with an emphasis on appropriate simplicity.
• Ability to break down ambiguous business questions into manageable plans identifying necessary data, quality thresholds, and stopping points.
• Comfort working with imperfect operational data, investigating outliers and data quality issues rather than bypassing them.
• Excellent communication skills, including translating technical methods and uncertainties for non-technical stakeholders; experience with Tableau or equivalent visualization tools is expected.
• Experience or exposure to consumer credit, PAYGo, lending, distribution, or supply chains is an advantage, especially where analysis informed operational decision-making.
• A passion for d.light's mission and customers, thriving in a dynamic startup environment requiring initiative to create process and structure.

Compensation and Benefits

• Competitive salary package
• Comprehensive medical coverage
• Pension benefits