Technical Lead — Data Science (f/m/x)

Our requirements

• At least 6 years in data science with a track record of models shipped to production, including a minimum of 2 years leading or mentoring other data scientists
• Deep, hands-on Python skills across the standard data stack (pandas, NumPy, scikit-learn, XGBoost) — you can still review and write the hard parts yourself
• Strong statistical and ML foundations: experimental design, validation methodology, and the judgment to spot results that won’t survive contact with reality
• Familiarity with at least one cloud/data platform and its data science components — Azure (Microsoft Fabric, Azure Machine Learning), AWS (SageMaker), GCP (Vertex AI, BigQuery ML), Snowflake (Snowpark ML, Cortex), Databricks (MLflow, Mosaic AI), or Palantir (Foundry Code Workspaces, Foundry ML, AIP)
• Experience leading delivery in a client-facing or consulting context: scoping, estimation, and managing technical risk
• Strong communication skills — able to defend a methodology to a technical audience and explain its business impact to a non-technical one
• Fluent English (both written and spoken)
• Fluent Polish required
• Residing in Poland required

Optional

• Production experience with Microsoft Fabric or Palantir Foundry, or relevant platform certifications
• Experience with MLOps at team scale: CI/CD for ML, model registries, monitoring, and governance
• Exposure to GenAI/LLM projects and judgment about where they do — and don’t — belong in a data science solution
• Public technical presence: conference talks, publications, or open-source contributions

Your responsibilities

• Own the technical direction of data science engagements: solution design, modeling approach, validation strategy, and delivery quality
• Lead and mentor a team of data scientists — code reviews, methodology reviews, career development, and raising the bar on what "done" means
• Stay hands-on: prototype approaches, unblock the team on hard modeling problems, and contribute production-grade Python where it matters most
• Translate client business problems into scoped, estimable data science workstreams, and push back when the problem doesn’t need a model
• Set and enforce engineering standards for the team: reproducibility, experiment tracking, testing, and documentation
• Guide platform decisions and delivery across cloud/data ecosystems — Microsoft Fabric, Palantir Foundry, Databricks, Snowflake, and native Azure/AWS/GCP services
• Work with AI Architects, data engineers, and client stakeholders to align technical decisions with business outcomes and timelines
• Represent the team in front of clients: present results, defend methodology, and manage technical expectations

About the project

This is how we work on a project

• Continuous Deployment
• Continuous Integration

What we offer

• AI Grant — Stop talking about AI and start building it. Our AI Grant gives you dedicated budget and resources to turn your wildest AI idea into a working project, backed by two paid weeks to focus on nothing else
• AI Center of Excellence — Work alongside specialists in agentic AI, sovereign AI, generative and discriminative AI. This isn’t a siloed team — it’s the people you’ll learn from and build with daily
• Your tools, your choice — Full access to AI-powered development tools including Claude, Cursor, and GitHub Copilot. Pick what works best for you
• Real project variety — From generative AI for legal document compliance, through agentic systems in manufacturing environments, to enterprise-scale AI platforms, computer vision, and autonomous driving. You won’t get bored
• Conference and speaking support — Want to attend conferences? We’ll back you. Want to speak at them? Even better — we’ll support you with dedicated preparation time and bonuses

Recruitment stages

• 1.
  Send your CV
• 2.
  Talk to us about your expectations
• 3.
  Learn more about our projects and choose the best
• 4.
  Start your adventure with Sii!

Sii Sp. z o.o.