National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Junior Data Scientist – Quantitative Market Research (Agency Side)

Echo Talent
London
5 days ago
Create job alert

Junior Data Scientist – Quantitative Market Research (Agency Side)

📍 Hybrid – London | £28,000–£30,000 | Full-time


We’re partnering with awell-established yet fast-evolving boutique analytics consultancythat specialises in providing quantitative research and data science solutions to both research agencies and end clients. This agency has recently become part of a growing insights group, giving them access to exciting new projects, strong infrastructure, and an innovative environment – while still retaining a friendly, close-knit culture.


This is a rare opportunity to join atight and highly capable data science team, working at the cutting edge of research analytics. Whether it's helping a major brand uncover customer segments, building conjoint simulations, or solving ad hoc analytical challenges, the work is varied and intellectually rewarding.


The Role

We’re looking for aJunior Data Scientist(graduate to 2 years' experience) with a strong quantitative background and a desire to grow within a collaborative team. You’ll work on full-service analytics projects, supporting everything from questionnaire design and fieldwork to deep data analysis and reporting.

Expect exposure to:

  • MaxDiff, segmentation, conjoint, and other advanced analytical methods
  • Key driver analysis, simulators, and ad hoc statistical problem solving
  • Designing and executing thequant elementsof research studies
  • Working inDisplayr(training provided), Excel, and other analytics tools
  • Creatingdashboards, insights reports, and internal tools to support clients


You’ll be supported by a small, smart team of Data Scientists and Directors who love what they do, and you’ll receive hands-on mentoring to quickly build up your capability.


What We’re Looking For

You might be a graduate with an internship, someone with up to 2 years’ experience in research or analytics, or a postgrad looking for your first commercial role.


Must-haves:

  • Comfortable withnumbers and data; strong analytical mindset
  • Confident inExceland able to pick up new software tools quickly
  • Aproblem-solver– curious, methodical, and eager to learn
  • Degree in a relevant subject (not limited to maths/stats – psychology, economics, neuroscience, etc. welcome)
  • Excellent communication skills and a team-focused approach


Bonus (not essential):

  • Internship or experience in market research / analytics
  • Knowledge of techniques like regression, segmentation, significance testing
  • Exposure to SPSS, R, Q, Sawtooth, Displayr, or similar platforms


Why Join?

  • Vibrant teamwith great culture – monthly socials, poker nights, London drinks
  • Flexible hybrid working– minimum 1 day/week in office
  • Highretention– people stay because they enjoy the work and the team
  • You won’t be siloed – work with multiple clients across many sectors
  • A chance to build a genuinecareer in data sciencewithin market research

Related Jobs

View all jobs

Junior Data Scientist – Quantitative Market Research (Agency Side)

Senior Data Scientist

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist

Senior Data Science Consultant – Econometrics specialist

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.