Data Scientist

Are you excited by solving real business problems with data, analytics, and AI?

Do you enjoy combining structured analysis, client interaction, and modern tools to create measurable impact?

Are you curious about new ways of working, including AI-assisted and agentic workflows, while staying pragmatic and quality-driven?

At Agilytic, we help clients turn business objectives into measurable results through smarter use of data. We are looking for a colleague who is comfortable moving between business understanding, quantitative analysis, and hands-on delivery.

What is your mission? Help innovative companies turn their objectives into concrete results through smarter use of data, analytics, automation, and AI.

You will work at the intersection of business and technology to help clients make better decisions, improve performance, and implement solutions that create tangible value.

What will you do day to day? As a Data Scientist (Consulting & AI Delivery), you will contribute to the end-to-end delivery of our projects, from problem framing to implementation and client adoption.

You will work closely with client stakeholders and internal team members to:

Translate business questions into analytical approaches and decision-support solutions

Structure and prioritize requirements with clients

Collect, clean, transform, and validate data from multiple sources

Perform descriptive, diagnostic, and predictive analyses where relevant

Build dashboards, models, reports, and decision-support tools

Prototype and automate parts of the analysis or delivery workflow

Communicate findings, trade-offs, and recommendations clearly to technical and non-technical audiences

Support implementation so that analysis leads to concrete action

Use modern AI-assisted tools responsibly to accelerate research, coding, testing, documentation, and delivery

Our assignments typically include:

Data audit

Data preparation

Descriptive and diagnostic analysis

Modeling where relevant

Dashboarding and reporting

Presenting results and recommendations

Supporting implementation and business adoption

Senior Data Scientists also supervise and coach junior team members in both client delivery and internal initiatives. This guidance helps them quickly develop the business, consulting, and technical skills needed to manage projects independently.

How we work We are pragmatic and outcome-driven. We use the right level of sophistication for the problem at hand.

That means we do not apply advanced techniques for their own sake. Sometimes the right answer is a predictive model, an automation, or a more advanced analytical workflow. Sometimes it is a clear dashboard, a robust dataset, or a simple analysis that helps a client act quickly and confidently.

Increasingly, this also includes AI-assisted and agentic ways of working. We welcome candidates who are already comfortable using tools such as Claude Code, Codex, GitHub Copilot, Cursor, or similar tools to accelerate research, coding, testing, documentation, and delivery.

What matters most is not tool usage alone, but professional judgment: being able to frame the problem correctly, validate outputs carefully, communicate clearly, and maintain quality, security, and maintainability.

Do you recognize yourself?Your background

You hold a master’s degree in a quantitative, scientific, engineering, or business-related field such as Engineering, Mathematics, Statistics, Economics, Physics, Biology, Computer Science, or similar

You are fluent in English and in either Dutch or French Your core skills

You have a strong foundation in analytics, statistics, and structured problem solving

You have hands‑on experience with Python and SQL for data preparation, analysis, and modeling

You are comfortable working with real‑world datasets and transforming ambiguous business questions into structured analytical work

You can communicate insights clearly and adapt your message to both technical and non‑technical audiences

You are comfortable working directly with clients and presenting recommendations Nice to have

Experience with ETL / ELT workflows, cloud data environments, APIs, or analytics engineering

Experience with BI and reporting tools

Familiarity with machine learning, forecasting, segmentation, optimization, or experimentation

Experience with version control, testing, and collaborative development practices

Familiarity with AI‑assisted or agentic coding workflows and tools such as Claude Code, Codex, GitHub Copilot, Cursor, or similar

We will be especially interested in candidates who can show how they use modern tools to work faster and better w