Research Data Scientist – Dashboards & Applications in Cambridge

Collect, process and clean data for analysis and visualisation.
Conduct data analysis using appropriate quantitative methods.
Design and build interactive visualisations and dashboards for technical and non-technical audiences using Shiny, Streamlit or similar.
Apply visual design principles to ensure clarity, accessibility and impact.
Use R or Python and business intelligence tools in data science work.
Develop data products such as interactive dashboards and APIs, including productionising machine learning models, statistical models and LLM capabilities as required.
Support integration of data science, quantitative research and AI into research proposals.
Identify opportunities to enhance research through data visualisation, dashboarding and interactive tools.
Support colleagues applying quantitative techniques to research and internal projects.
Guide teams in using dashboards and visual analytics.
Contribute to multidisciplinary projects, including shared dashboards, visualisation frameworks and APIs.
Create solutions to complex research problems through interactive tools and visual analytics.
Develop and maintain reusable dashboards and data products using Shiny, Streamlit, Power BI, Tableau or custom web applications.
Build and document APIs and data services using Plumber or FastAPI.
Create data and AI products supporting policy analysis and decision-making.
Improve business processes through monitoring and reporting dashboards.
Apply visual storytelling practices to improve accessibility of research and policy design.
Embed data science and visual analytics into wider policy research activities.
Follow and help refine standards for data handling, reproducible code, version control, peer-review/client outputs, and dashboard accessibility.
Work with researchers to improve research using statistics, AI and data science techniques.

Requirements

• Experience conducting quantitative research, from designing an approach to a problem through to delivering analysis.
• Enthusiasm to learn and solve complex problems.
• Proficiency in writing clean, reproducible code for data processing, analysis and visualisation in Python or R.
• Experience handling data, including cleaning, manipulation and linking.
• Ability to visually represent data, including experience designing interactive dashboards or visual analytics for different audiences.
• Experience building data-driven web applications or dashboards using tools such as Shiny, Streamlit, Tableau or Power BI.
• Understanding of basic visual design principles (e.g. chart selection, colour use, information hierarchy) and their application to data visualisation.
• Ability to communicate findings and approaches to research, both written and verbal, tailored to different audiences.
• Ability to work as part of a team.
• An analytical mindset and attention to detail.
• Proficiency in Microsoft tools such as Outlook, Teams, Excel, Word and PowerPoint.
• Degree level qualification in a quantitative field or equivalent practical experience.
• Experience using Git or other version control systems.
• Proficiency in HTML, JavaScript, CSS, SQL, Tableau or Power BI is advantageous.
• Experience developing RESTful APIs or data services using Plumber or FastAPI.
• Experience with data storytelling and UX considerations in dashboard design.
• Experience with LLMs, prompt engineering or AI evaluation frameworks.
• Familiarity with AWS, Azure, GCP and containerisation tools such as Docker or Podman.
• Experience in Linux/Unix environments.
• Working understanding of the end-to-end ML development process.
• Published works in data science, statistics or other numerical disciplines.
• Sole UK national; successful completion of SC clearance before commencing and willingness and eligibility to apply for DV clearance upon joining.

Core Competencies

Demonstrates expertise in data analysis, visualisation, and the development of interactive dashboards using R or Python. Proficient in applying visual design principles and communicating complex findings to diverse audiences.

Highest-signal resume keywords

• Data Analysis
• Interactive Dashboard Development
• R or Python Proficiency
• Visual Design Principles
• API Development

Hard Skills

• Data Cleaning
• Data Manipulation
• Quantitative Research
• Machine Learning Models
• Statistical Models
• Data Visualisation
• Reproducible Code
• RESTful APIs
• SQL
• Version Control

Soft Skills

• Analytical Mindset
• Attention to Detail
• Team Collaboration
• Problem Solving
• Communication Skills

Industry Keywords

• Data Science
• Visual Analytics
• Data Storytelling
• Policy Analysis
• AI Evaluation Frameworks

Tools & Technologies

• Shiny
• Streamlit
• Tableau
• Power BI
• Plumber
• FastAPI
• HTML
• JavaScript
• CSS
• Microsoft Office Suite