Data Scientist (Uk)

We’re looking for a passionate Data Scientist who enjoys solving real business problems with data and machine learning. You’ll take part in designing and delivering ML solutions end-to-end — from exploration and experimentation to deployment. If you like working with diverse data, collaborating with others, and seeing your models used in production, we’d love to meet you!

You will be responsible for:

• Designing and developing CV/ML/AI models (predictive, classification, recommendation, LLM-based),
• Selecting and optimizing algorithms (regression, tree-based, neural networks, etc.),
• Integrating models into production environments,
• Performing data cleaning, feature engineering, and model validation,
• Collaborating with clients and internal teams to translate analytical results into actionable insights,

Qualifications

• 3 + years of experience in data analysis, computer vision, machine learning, or statistical modeling,
• Practical experience with ML model deployment (on cloud or on-premise),
• Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow),
• Understanding of Windows or Linux software development platforms
• Good understanding of statistics and data preparation,
• Working knowledge of SQL and version control tools (Git),
• Fluent English – for international communication and collaboration.

Additional Information

Nice to have:

• Experience with LLMs, or Time Series,
• Familiarity with tools like Docker, MLflow, Airflow, AWS/GCP/Azure,
• Background in research or R&D,
• Experience working in cross-functional or international teams.

Soft Skills:

• Curiosity and problem-solving mindset,
• Clear communication and teamwork,
• Proactive attitude and sense of ownership,
• Ability to explain technical concepts to non-technical audiences.

What We Offer:

• Exciting projects in AI and ML with real-world impact,
• Collaboration with international clients (US and Europe),
• Hybrid working model – 3 days per week in the office, with the option to work remotely on the remaining days,
• Supportive, growth-oriented culture that values innovation.

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