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Junior Data Scientist – Fully Remote (UK-Based Only)
💰 £35,000 – £50,000 DOE
We’re working with a fast-growing analytics and technology business in the media and entertainment sector, helping global streaming brands unlock the power of their data.
This is a hands-on opportunity to join a small, ambitious team and work across the full data science stack — from data engineering and model development to insight generation and deployment. You’ll gain exposure to real-world AI and ML applications across text, images, and time-series data, with the freedom to experiment, innovate, and make an immediate impact.
What You’ll Do
- Design and build predictive models using time-series, NLP, and computer vision techniques.
- Work end-to-end on data science projects — from ETL and feature engineering to model evaluation and insight delivery.
- Create clear, actionable reports and visualisations that translate data into business impact.
- Support the development of automated data pipelines and quality monitoring tools.
- Collaborate closely with technical and non-technical teams to bring ideas from concept to production.
What You’ll Bring
- 1+ year of commercial Data Science experience.
- Strong proficiency in Python (pandas, NumPy, scikit-learn) and SQL.
- Solid grasp of statistics, data wrangling, and forecasting.
- Strong communication skills — able to explain models and results in simple, practical terms.
- Curiosity and creativity when it comes to solving data problems.
- Must be UK-based with full right to work (no visa sponsorship).
Why You’ll Love It Here
🚀 Direct exposure to live AI and ML projects in NLP, forecasting, and computer vision.
🎯 End-to-end ownership of projects and real business impact.
💡 Collaborative, startup-style culture with plenty of autonomy.
🏠 Fully remote within the UK.
💸 Competitive salary £35,000–£50,000 + growth opportunities.
If you’re passionate about data, love building models that make a difference, and want to grow in a creative, data-driven team — this could be your next big move.
Key Skills
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