Data Scientist

Syensqo is all about chemistry. We're not just referring to chemical reactions here, but also to the magic that occurs when the brightest minds get to work together. This is where our true strength lies. In you. In your future colleagues and in all your differences. And of course, in your ideas to improve lives while preserving our planet's beauty for the generations to come.

Job title

• - Data Scientist

Job overview and responsibilities

• Syensqo is a leading multinational materials company headquartered in Brussels, advancing humanity through scientific exploration and innovation. Nearly two years after the spin-off from Solvay, has evolved from inception to a nimble, high-impact scale-up that accelerates AI adoption across the Group—partnering closely with corporate functions (e.g., Finance, HR, Legal, Procurement), operations, and our chemists and researchers.

We operate lean and fast, with a startup mindset and strong governance: deliver impact quickly, build responsibly, and meet enterprise standards for security, compliance, ethics, and guardrails.

As a Data Scientist, you will design experiments and productionize machine learning and generative AI capabilities on Azure, focusing on measurable business outcomes, reproducibility, and MLOps best practices. You will collaborate directly with stakeholders, guide technical decisions, and help shape patterns and standards for agentic AI within the enterprise.

This role will focus on SyGrow. SyGrow is 's sales copilot initiative. In this role, you will turn sales and stakeholder needs into data products—exploring new features, validating hypotheses, and shipping ML- and LLM-powered capabilities that drive commercial impact. You balance fast iteration with enterprise-grade practices in data, MLOps, and Responsible AI.

The position reports to the SyGrow AI Lead.

Key Responsibilities:

• Explore and prototype new SyGrow features from hypotheses to validated experiments with measurable outcomes.
• Translate sales and stakeholder needs into analytical problems, KPIs, and success criteria.
• Build, evaluate, and iterate ML models for recommendations, scoring, forecasting, and insights.
• Implement robust data ingestion, feature engineering, and training pipelines in Azure ML and Microsoft Fabric.
• Productionize models with CI/CD, versioning, telemetry, and rollback using Azure DevOps.
• Leverage LLMs (prompting, RAG) to augment the sales copilot; define guardrails and evaluation strategies.
• Ensure privacy, security, and compliance across data and model lifecycles.
• Monitor performance, drift, and cost; run A/B tests and incorporate user feedback.
• Collaborate with engineering and product to ship incremental value in agile sprints.
  
  Document decisions, share knowledge, and contribute reusable components and templates.
• Integrate with CRM/BI workflows and data sources to operationalize outcomes.
• Mentor interns/juniors and champion best practices in Data Science and MLOps.

Education and experience

• Education: Master's in Data Science, Computer Science, Engineering, Mathematics, or related field — or equivalent practical experienc

• Experience

• 2–5 years' hands-on experience delivering ML/DS solutions from exploration to production.

• Partnered with business stakeholders (preferably sales/commercial).
• Implemented MLOps on Azure.
• Worked in agile teams.

Technical Knowledge:

• • Python; scikit-learn; PyTorch;
• Transformers; experimentation and evaluation;
• RAG and prompt engineering;
• Azure Machine Learning; Azure OpenAI / Azure AI Foundry;
• Azure AI Search; Azure Data Factory; Azure DevOps;
• Microsoft Fabric;
• containers (Docker; AKS/Container Apps);
• data engineering fundamentals (SQL/ETL/APIs);
• monitoring and cost governance.

Skills and behavioral competencies

• Startup mindset & ownership: proactive, autonomous, resourceful, bias to action.
• Business impact orientation: frames problems, defines KPIs, measures value, iterates quickly.
• Collaboration & knowledge sharing: partners across Sales, Product, Engineering; contributes reusable assets.
• Communication: explains complex topics clearly to non-technical stakeholders.
• Curiosity & craftsmanship: keeps pace with ML/LLM advances; adopts what works.
• Responsible AI: builds with security, privacy, and compliance by design.
• Strong programming discipline: testing, code reviews, documentation, CI/CD.

Language skills

• English (mandatory)
• French (nice to have)

What's in it for the candidate

• Be part of — and contribute to — a once-in-a-lifetime transformation at Syensqo: small, empowered team; direct line of sight to impact; modern Azure stack; autonomy to ship meaningful AI products used across the Group.

About us

• Syensqo is a science company developing groundbreaking solutions that enhance the way we live, work, travel and play. Inspired by the scientific councils which Ernest Solvay initiated in 1911, we bring great minds together to push the limits of science and innovation for the benefit of our customers, with a diverse, global team of more than 13,000 associates. Our solutions contribute to safer, cleaner, and more sustainable products found in homes, food and consumer goods, planes, cars, batteries, smart devices and health care applications. Our innovation power enables us to deliver on the ambition of a circular economy and explore breakthrough technologies that advance humanity.
• At Syensqo, we seek to promote unity and not uniformity. We value the diversity that individuals bring and we invite you to consider a future with us, regardless of background, age, gender, national origin, ethnicity, religion, sexual orientation, ability or identity. We encourage individuals who may require any assistance or accommodations to let us know to ensure a seamless application experience. We are here to support you throughout the application journey and want to ensure all candidates are treated equally. If you are unsure whether you meet all the criteria or qualifications listed in the job description, we still encourage you to apply.

LI-IJ1LI-OnsiteJunior