Research Data Scientist – Dashboards & Applications

Jobtailor

Cambridge

On-site

GBP 60,000 - 90,000

Full time

3 days ago

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Job summary

Jobtailor in Cambridge seeks a data-focused professional to collect, process, and visualise data, building interactive dashboards for technical and non-technical audiences using R or Python. You will develop data products, APIs, and productionise ML/LLM capabilities while aligning with policy research needs.

You will collaborate with researchers, applying visual storytelling and UX considerations to dashboards, and contribute to multidisciplinary projects across data science and AI.

Qualifications

Experience conducting quantitative research from design to delivery.
Proficiency in clean, reproducible code for data processing and analysis in Python or R.
Experience designing interactive dashboards for diverse audiences.
Experience building dashboards/web apps with Shiny/Streamlit/Tableau/Power BI.
Understand visual design principles for data viz.
Ability to communicate findings to varied audiences.
Experience with RESTful APIs or data services.
Familiarity with cloud platforms and containerization (AWS/Azure/GCP, Docker).
Experience with LLMs and AI evaluation frameworks.
Published works in data science or statistics.
UK national; willingness to apply for DV clearance.

Responsibilities

Develop dashboards and data products using Shiny, Streamlit, Tableau or Power BI.
Build and document APIs/data services (Plumber/FastAPI).
Productionise ML models and AI capabilities where required.
Collaborate with researchers to integrate data science into proposals.
Guide teams on dashboards and visual analytics usage.
Create scalable data visualization solutions for policy analysis.
Ensure reproducible code, version control and accessibility standards.

Skills

Quantitative research

Python or R

Data cleaning

Data manipulation

Data visualisation

Interactive dashboards

RESTful APIs

Git / Version control

LLMs & AI eval

Cloud + Docker

Education

Quantitative degree

Tools

Shiny

Streamlit

Tableau

Power BI

Plumber

FastAPI

HTML

JavaScript

CSS

SQL

Docker

Job description

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.

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