Data Scientist – Decision Science, Modelling

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Design, develop, and sustain statistical, probabilistic, and simulation-based models.

• Convert complex business inquiries into manageable modeling challenges.

• Choose suitable modeling techniques based on the problem's characteristics instead of methodological bias.

• Create prototypes and functional solutions iteratively, adjusting methods as new data becomes available.

• Construct analytical assets that can be repurposed as products, decision-support tools, or operational capabilities.

• Design and analyze experiments to assess interventions, operational modifications, and model performance.

• Effectively handle incomplete, imperfect, and evolving datasets.

• Formulate strategies for estimating missing data and integrating evidence from diverse sources.

• Measure uncertainty and effectively communicate the confidence in model outputs.

• Evaluate assumptions and pinpoint limitations within modeling strategies.

• Develop frameworks that enhance operational and commercial decision-making.

• Assess alternative actions, trade-offs, and potential results.

• Aid in automating suitable decision-making processes through analytical models.

• Design experiments and simulations that guide strategic and operational decisions.

• Validate models using appropriate testing, back-testing, and comparison methodologies.

• Examine sensitivity to assumptions and variations in conditions.

• Monitor model performance over time and detect concept drift or degradation.

• Uphold high standards of analytical rigor and reproducibility.

• Collaborate closely with Business Analysts, Engineering, Product, and operational teams.

• Clearly articulate modeling approaches, assumptions, and results to non-technical audiences.

• Document methodologies, limitations, and recommendations in a practical and accessible manner.

• Foster a culture of experimentation and evidence-based decision-making.

• Design models and analytical strategies with operational implementation in mind.

• Work in tandem with Engineering teams to convert models into scalable production solutions.

⛳️ Requirements

• Solid foundation in applied statistics, modeling, data science, operational research, economics, mathematics, or a related quantitative field.

• Experience in developing models that support real-world decisions, products, or operational processes.

• Familiarity with managing uncertainty, incomplete information, and imperfect datasets.

• Capability to transition from loosely defined problems to actionable analytical solutions.

• Strong skills in problem decomposition and structured thinking.

• Ability to explain technical concepts clearly to non-technical stakeholders.

• Proficient coding skills in Python or R.

• Experience in developing analytical solutions in code rather than primarily through spreadsheet-based methods.

• Proven track record of taking analytical models from prototype to operational deployment.

🏝️ Benefits

• 25 days of annual leave

• Participation in a company bonus program linked to individual and company performance

• Group Life Cover at 4x salary

• Pension contributions of 4% from both employee and employer

• Vitality benefits following probation

• Employee discount program

• Discounted gym membership