Data Scientist - Supply Chain (Procurement & Product Costing)

Corvus People
Belfast, County Antrim, United Kingdom
Today
£50,000 – £70,000 pa

Salary

£50,000 – £70,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Mid
Education
Degree
Posted
5 May 2026 (Today)

Role: Data Scientist – Supply Chain (Procurement & Product Costing)

About the Role

We are seeking a Data Scientist to join our Supply Chain Data Team, working closely with Procurement. The initial focus of this role is to develop pragmatic, decision‑enabling analytics and data science tools that support key procurement activities, including:

Product cost roadmaps (for both new product introductions and established products)

Product cost controls

Product cost reduction initiatives

The role requires a practical mindset: working with multiple data sources of varying completeness and quality, balancing analytical rigour with business reality to deliver insights that are useful, timely, and trusted. Over time, the role will expand into broader procurement analytics use cases.

Key Responsibilities

Design and build analytical and predictive tools that enable product cost roadmaps, helping procurement teams understand how product costs are expected to evolve over time and why

Develop models and monitoring tools to support product cost controls, including identifying variances, emerging risks, and cost pressures

Create data‑driven analyses to identify and quantify opportunities for product cost reduction

Analyse and explain the drivers of cost changes, going beyond transactional data to account for upstream supply chain impacts, supplier and market dynamics, external data enrichment, and macro‑economic or geopolitical influences.

Work with data from multiple internal and external sources, often with incomplete, inconsistent, or imperfect data, applying pragmatic assumptions and transparent methods

Perform scenario and sensitivity analysis to support negotiations, sourcing strategies, and planning decisions

Clearly document and communicate model assumptions, data limitations, and confidence levels so stakeholders understand both insight and uncertainty

Apply data science techniques to additional procurement use cases as needs evolve

Partner closely with procurement stakeholders to ensure analytics are aligned to real decision‑making processes

Contribute to reusable models, data assets, and practical analytics standards within the Supply Chain Data Team

Essential Skills & Experience

Strong data science capability, including statistical analysis and predictive modelling

Proven experience building costing, financial, or commercial models, ideally in procurement or supply chain contexts

Advanced proficiency in data preparation, analysis and modelling, including model explainability methods

Advanced proficiency in Python, SQL. Familiarity with Snowflake.

Demonstrated ability to work pragmatically with messy, incomplete, or low‑quality data, making sound judgement calls rather than waiting for “perfect” datasets

Experience integrating and reconciling data from many sources with differing definitions and levels of maturity

Ability to clearly explain analytical outputs, assumptions, and limitations to business stakeholders

Strong commercial awareness and a business‑focused approach to analytics

Desirable / Nice to Have

Experience using Dataiku

Understanding of procurement contracts, pricing mechanisms, and cost structures

Experience working closely with procurement or finance teams

Related Jobs

View all jobs

Data Scientist

Faculty AI London, United Kingdom
Hybrid

Data Scientist

Vertical Aerospace Bristol, United Kingdom
Permanent

Data Scientist

Adaptable Recruitment Liverpool, United Kingdom
£50,000 – £60,000 pa Hybrid

Data Scientist

Searchability NS&D Cheltenham, United Kingdom
£45,000 – £75,000 pa Permanent Clearance Required

Data Scientist

Hays Technology London, United Kingdom
£600 – £1,000 pd

Industry Insights

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

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

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.