Data Scientist – Machine Learning & Generative AI

I am helping my client hire a Data Scientist (3–5 years experience) to join them — a long-established tech partner powering fast-growing European internet companies.

If you enjoy owning the full data science lifecycle — from modelling and experimentation to production deployment — this could be a great fit.

💡 Why us?

• Founded 10+ years ago, trusted by multiple high-growth European internet companies

• Long-term client partnerships with steady business growth

• Real large-scale systems — handling 70K–280K QPS

• Strong work-life balance — most engineers finish around 6pm

• Stable, low-turnover team (many engineers stay 3+ years)

• Talents from ByteDance, Bybit, Xiaohongshu, Tencent, Shopee and Kuaishou have joined and stayed long-term

• Supportive and collaborative engineering culture

🎯 What you’ll work on

• Build statistical and machine learning models on PB-scale data

• Design experiments (A/B testing, causal inference) to drive product and business decisions

• Develop and maintain production-grade MLOps pipelines

• Translate complex data insights into actionable recommendations

• Explore cutting-edge AI / Generative AI technologies

• Build scalable big data pipelines to support data science projects

✅ We’re looking for someone who

• Has 3–5+ years of Data Science / ML experience

• Can independently handle the end-to-end DS workflow (modelling → analysis → production)

• Strong fundamentals in SQL & Python

• Experience deploying ML / DL models in production

• Comfortable with large-scale data (Hadoop / Spark / Hive)

• Familiar with TensorFlow or PyTorch

• Solid understanding of experimentation & A/B testing

• Curious, proactive, and eager to continuously learn

➕ Nice to have

• Experience with LLMs, RAG, or fine-tuning

• Familiarity with GenAI tooling (HuggingFace, LangChain, etc.)

• Recommendation systems or e-commerce domain experience

• Large tech company background

We value strong data science fundamentals and learning agility — technologies evolve, and so do we.