Mission Overview:
Keystone Solutions is seeking a Senior Data Scientist for a consultancy mission at a client site. This role involves accelerating strategic data initiatives through expertise, technical direction, and coaching, while managing a continuous stream of ad-hoc data requests by prioritizing and translating them into reusable solutions and data products.
Core Responsibilities:
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Strategic Projects & Technical Leadership: Take the technical lead in complex data projects (e.g., advanced analytics, graph/network analytics, integrations, architectural choices). Shape the approach, solutioning, and priorities of larger initiatives with a focus on feasibility, impact, and scalability. Ensure and promote quality standards, including reproducibility, documentation, methodology, and engineering quality where relevant.
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Team Uplift & Co-Creation: Coach and guide data scientists and analysts through co-creation, content reviews, and sharing best practices. Contribute structurally to enhancing team competencies (methodology, approach, quality, communication). Actively participate in developing team agreements, such as definition of done, work formats, and knowledge sharing.
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Structuring and Productizing Ad-Hoc Requests: Create an overview of incoming requests: intake, slicing, prioritization, status/communication. Cluster ad-hoc work and convert it into structural, reusable solutions (reusable datasets, analysis methods, templates, data products). Apply FAIR principles from a data product perspective with a focus on reusability and quality.
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Project Management & Follow-Up: Take on basic delivery/project follow-up (scope, milestones, dependencies, risks). Support the team leader in follow-up and coordination to bring stability to planning and execution. Contribute to stakeholder alignment, including expectation management, decision-making, and escalations when necessary.
Collaboration & Stakeholders:
Work closely within the Data Mining team (data scientists/analysts, and where relevant data engineers/platform stakeholders). Collaborate with the Data Platform team and content partners/stakeholders. Operate in an environment with multiple priorities, requiring structure in intake, follow-up, and communication.
Profile (Must-Haves):
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Master's degree in IT.
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Strong hands-on experience as a Data Scientist / ML Engineer with a focus on Python.
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Experience with data analysis and modeling (pandas, scikit-learn) and building/improving ML models in a production context.
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Strong software engineering foundation: Git, code reviews, CI/CD pipelines, Docker; experience in setting up APIs and reusable components (e.g., FastAPI).
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Knowledge of SQL; experience with infrastructure-as-code or cloud is a plus (Terraform, AWS/GCP).
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Strong ability to structure unclear questions and translate them into concrete approaches/deliverables.
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Experience with coaching/mentoring and working in co-creation (e.g., technical training, reviews, SCRUM/scrum master role).
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Strong communication skills (engaging stakeholders, clear reporting, managing expectations).
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Trilingual (NL/FR/EN) strongly desired, preferably at a high level.
Plus Points (Nice-to-Haves):
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Experience with data product thinking, governance, and quality principles (FAIR, definitions, documentation, reusability).
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Experience with graph analytics/network analytics or other advanced analytics domains.
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Knowledge of Databricks.
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Previous experience within an OISZ is a significant plus.
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Previous experience with secondary data use and fraud detection.
Expected Impact (3-6 months):
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Clearer intake and prioritization process for ad-hoc requests to the Data Mining team.
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More reusable and scalable outputs instead of one-offs.
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Measurable uplift in team quality through coaching, reviews, and methodological agreements.
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Better predictability and progress on key data projects and strategic initiatives.
If you are ready to tackle technical and strategic challenges in a dynamic consultancy environment, apply today .
Duration: 22/06/2026 - 31/12/2026 7 months • (full time)
Language requirements:
Dutch
Level Active knowledge
English
Level Active knowledge
French
Level Active knowledge
