Senior Data Scientist

Bridgewater Resourcing Solutions Limited
Manchester
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist (GenAI)

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Data Science Consultant – Contract with genuine potential for extensions


Location:Hybrid (On-site workshops in Manchester, remote working for development/testing)


Contract Type:Fixed-term consultancy contract (with potential for further work)


About our client: Rove:


  • At Rove, we’re on a mission to help consumer brands expand into international markets faster, cheaper, and more strategically.
  • We’re an early-stage startup with big ambitions, and we’re building a proprietary “Rove Score” – a data-driven framework to pinpoint the best global opportunities for brands based on a vast and varied range of datasets.


What We Need from our experienced Data Scientist:


  • We’re looking for a Data Science expert who can roll up their sleeves and help shape one of the core innovations of our product.
  • This is a knotty, complex challenge – how do you reliably score international market opportunities for brands when there’s so much data to absorb, interpret, and turn into actionable insights?


You’ll be working with us at Rove to:


  • Develop and refine the Rove scoring methodology: Incorporate diverse data sources (our own data, third-party APIs, SaaS platforms, and AI-driven outputs) to generate a robust, scalable scoring system.
  • Augment and enrich data sets: Identify clever ways to blend disparate data points to infer meaningful outcomes, ensuring we can handle complexity and variability without compromising on reliability.
  • Workshop & scope the challenge: Attend in-person sessions in Manchester to understand the product useful.
  • Collaborative but self-sufficient vision, define project scope, and plan the data strategy.
  • Test & iterate: Put the scoring system through its paces with multiple scenarios, identifying potential gaps, refining approaches, and ensuring repeatability and consistency.


What you need to bring as a Data Scientist for Rove:


  • Proven data science expertise: You’ll have demonstrable experience in building, refining, and validating complex data models.
  • Skilled in data augmentation & inference: You know how to leverage diverse data sources to infer trends, patterns, and outcomes.
  • Problem-solver at heart: You thrive on complexity and love turning messy data into something neat, logical, and instantly: Comfortable leading workshops and collaborating closely with the founding team, while also able to work independently to deliver results.
  • Inspiring & entrepreneurial: You’re excited by the early-stage startup environment, where your contributions can truly shape a product’s trajectory and differentiation.


Why Work With Us at Rove?


  • High-impact opportunity: You’ll be instrumental in defining one of our key USPs.
  • Flexibility: Workshops in person but the majority of the project can be done remotely.
  • Potential for more: While this is initially a fixed-term engagement, there’s room to continue if it’s a great fit on both sides.


If you’re excited by the idea of turning messy global data sources into a crystal-clear scoring system that guides consumer brands to their next big international leap, we’d love to hear from you.


Please note that we will NOT accept unsolicited headhunter / agency resume's. Rove will not pay any third-party agency or company that does not have a signed agreement with Rove.

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 Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.