Product Data Scientist

Randstad Technologies Recruitment
City of London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Product Data Scientist

Product Data Scientist

Product Data Scientist: Platform & Device Risk Analytics

Product Data Scientist: Shape Product Strategy with Data

Product Data Scientist — Lead Product Metrics & ROI

Product Data Scientist (London or New York)

Product Data Scientist

Location: Remote - UK
Type of role- 6 Months contract with potential extension
Payrate - 435 Per Day - 590 Per Day Inside IR35


We're looking for experienced Senior Data Scientists to join a leading global streaming and technology platform, supporting their product, design, and engineering teams.


What You’ll Work On

  • Designing and analysing A/B experiments across high-visibility product surfaces
  • Creating success metrics and shaping data-driven measurement strategies
  • Deep analytical work using SQL (BigQuery) + Python/R
  • Building dashboards in Tableau / Looker Studio
  • Delivering clear, actionable insights to senior stakeholders
  • Supporting either the User Platform (login, account systems, identity management).

What We’re Looking For

  • 5+ years as a product-focused Data Scientist
  • Strong background in A/B testing and experimentation
  • High proficiency in SQL (BigQuery preferred)
  • Skilled in Python or R
  • Excellent communication and stakeholder management
  • Experience working in fast-paced consumer tech or streaming environments is a strong plus

This is an urgent vacancy where the hiring manager is shortlisting for an interview immediately. Please apply with a copy of your CV or send it khushboo. Co. uk


Randstad Technologies is acting as an Employment Business in relation to this vacancy.


#J-18808-Ljbffr

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.