Data Scientist

CONTEXT

An ambitious matching platform is entering a new phase where algorithmic power is no longer enough: people need to understand, trust, and act on the results. The program is looking for a data scientist who can bridge the worlds of matching logic, interface design, and operational decision-making. The mission focuses on the front-end layer and results presentation, with the goal of making complex recommendations feel clear and usable inside a CRM environment. This is a role for someone who likes turning scores, rules, and signals into a story that operational teams can follow, while also keeping one foot in the engine room to improve the underlying models and workflows.

ACTIVITIES

• Design and refine interfaces that present matching results in a clear, actionable way.
• Build explainability features that show why a match was proposed and how confident the system is.
• Create monitoring dashboards to track match quality, adoption, and operational performance.
• Integrate presentation flows and result views into Microsoft Dynamics CRM.
• Contribute to the ongoing development of the matching engine and its data pipelines.
• Document design decisions, model behaviour, and operational procedures.
• Support evolutionary maintenance and provide guidance until the end of the program horizon.

EXPECTED ACHIEVEMENTS

• A results experience that is intuitive for business users and trusted by operational teams.
• Clear explainability that reduces black-box effects and accelerates adoption.
• Dashboards that surface the right signals for continuous improvement.
• A smoother connection between the matching engine and the CRM ecosystem.
• A documented and maintainable solution that stays useful well beyond the initial rollout.

ENVIRONMENT

• Microsoft Azure, Azure AI Search, Microsoft Fabric, and Microsoft Dynamics CRM.
• Front-end and data visualization work alongside Python-based data science workflows.
• Matching engine operations, explainability, monitoring dashboards, and evolutionary maintenance.
• A collaborative team focused on knowledge sharing, documentation, and long-term support.