Pricing Optimisation Data Scientist

Harnham - Data & Analytics Recruitment
London
2 months ago
Applications closed

Related Jobs

View all jobs

MOTOR INSURANCE PRICING PRACTITIONER / DATA SCIENTIST

Data Architect - Bristol - Hybrid Opportunity

AWS Data Engineer (contract)

Data Analyst ( hybrid) 3 days in office

Data Analyst | FTC

Data Analyst

Pricing Optimisation Data Scientist

£600-700 per day

Inside IR35

3 months

The Role

As a Pricing Optimisation Data Scientist, you will work closely with product, commercial, and engineering teams to design, build, and deploy pricing models. You will analyse large datasets, run experiments, and deliver actionable insights that directly impact business performance.

Key Responsibilities

  • Develop and maintain pricing optimisation models using Python and SQL
  • Analyse customer behaviour, demand elasticity, and price sensitivity
  • Design and evaluate A/B tests and pricing experiments
  • Build data pipelines and analytical datasets to support pricing decisions
  • Translate complex analytical results into clear insights for stakeholders
  • Collaborate with product managers and engineers to implement pricing changes
  • Monitor pricing performance and continuously improve models

Required Skills & Experience

  • Strong experience as a Data Scientist or Pricing Analyst in a commercial or tech environment
  • Advanced SQL skills for querying and transforming large datasets
  • Strong Python experience (e.g. pandas, numpy, scikit-learn, statsmodels)
  • Solid understanding of pricing theory, optimisation, and experime...

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.