At a Glance
- Tasks: Design and deploy advanced algorithms for predictive optimisation and recommendation models.
- Company: Join a leading Global Technology Division focused on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on statistical rigor and algorithmic fairness.
- Why this job: Make a real impact by optimising enterprise operations with cutting-edge data science techniques.
- Qualifications: Intermediate experience in data science and mastery of Python required.
The predicted salary is between 50000 - 70000 £ per year.
We are seeking a Data Scientist to join our Global Technology Division. This role sits within a highly strategic engineering team focused on predictive enterprise optimization and internal mobility platforms. You will hold the keys to a core mathematical engine, designing and deploying sophisticated recommendation models and matching indexes that mathematically balance complex business constraints against corporate operational overhead.
Key Responsibilities
- Algorithm & Index Design: Develop, tune, and maintain semantic matching algorithms, recommendation engines, or Natural Language Processing (NLP) models to map unstructured text profiles against highly technical corporate frameworks.
- Predictive Optimisation Modeling: Build mathematical optimization models evaluating personnel distribution variables alongside geographic constraints and operational cost parameters to calculate cost-effective resource strategies.
- Upholding Statistical Truth: Champion mathematical and statistical rigor. Ensure all machine learning models accurately handle data imbalances, control for historical performance biases, and rigorously evaluate algorithmic fairness.
- Collaborative AI Deployment: Work closely with upstream data teams to track model metrics, monitor algorithmic prediction drift, and safely surface confidence scores to executive decision-makers.
Required Technical Skills
- Experience: Intermediate experience as a Data Scientist, Machine Learning Engineer, or Quantitative Analyst within an enterprise environment (Fintech, Banking, or Scale-up SaaS preferred).
- Python Mastery: Complete fluency in Python and specialized machine learning/statistical libraries (scikit-learn, SciPy, statsmodels). Hands‑on exposure to NLP frameworks or text embeddings (spaCy, HuggingFace) is highly valued.
- Statistical Rigor: A solid foundation in applied statistics, including clustering, regression architectures, and predictive modeling validation techniques.
- Exploratory Data Storytelling: Ability to visually explain algorithm performance trends (using Plotly, Seaborn, etc.) and present model logic transparently to senior management.
We think you need these skills to ace Data Scientist in Sheffield
Algorithm Design
Index Design
Natural Language Processing (NLP)
Predictive Optimisation Modeling
Statistical Rigor
Machine Learning
Python
