Data Scientist

Impactive are exclusively partnered with a Leeds-based Data & AI consultancy that turns messy, complex data into decisions people can actually use.

They’re expanding their team and are hiring a mid-level Data Scientist, based in Leeds City Centre with a hybrid setup (2 days per week in-office).

Their work sits at the intersection of data science, machine learning, and real-world problem solving. They help organisations ask better questions of their data, and then build the models, tools, and insight to answer them.

They're big believers that great results come from a smart mix of technology and humans who know how to use it. No hype, no black boxes for the sake of it - just thoughtful, practical applications of data and AI that deliver impact.

This consultancy work with a growing portfolio of established organisations across multiple industries, partnering closely with client teams to tackle some genuinely interesting problems.

You’re the kind of person who enjoys getting your hands dirty with data, but also likes stepping back to ask “what problem are we actually trying to solve here?”

You’ll likely have:

• 2+ years’ experience working in data science.
• Comfortable wrangling large datasets in cloud-based data platforms.
• A self-starter mindset - you’re comfortable teaching yourself new tools, techniques, or approaches when needed.
• The ability to stay calm (and curious) when requirements change - because in consultancy, they will.
• An appetite for a fast-moving, consultancy-style environment where no two projects look quite the same.
• A relevant degree or equivalent practical experience in a quantitative or computational discipline, with solid foundations in statistics and programming.

You’ll be embedded in client delivery from day one, initially working in a BigQuery-based environment, with opportunities to support other data platforms over time.

In practice, that means you’ll:

• Design, build, test, and deploy data science and machine learning models inside client data environments.
• Create prototypes and proof-of-concepts to explore ideas, test assumptions, and shape future solutions.
• Translate fuzzy business questions into clear analytical approaches, models, and success metrics.
• Work in an agile delivery setup where iteration, feedback, and improvement are part of the job.
• Provide both tactical and strategic data science support to help clients get real value from their data.
• Sweat the details - with strong quality control, validation, and reproducibility baked into your work.
• Collaborate closely with teammates, sharing ideas, challenging assumptions, and helping each other deliver great work.

You’ll combine strong technical foundations with the ability to communicate clearly and deliver pragmatically in varied client environments.

• Strong analytical and problem-framing skills - you can turn ambiguous questions into testable hypotheses and robust analyses (essential).
• Excellent Python and SQL skills (essential).
• Hands-on experience with common Python data science and machine learning libraries (e.g. pandas, scikit-learn, and friends) (essential).
• Experience using version control (e.g. Git) to collaborate and manage code sensibly (essential).
• Experience working with large-scale data and cloud platforms such as BigQuery, Snowflake, or Databricks (nice to have).
• Experience designing and deploying machine learning workflows in cloud environments (nice to have).

• You communicate clearly, listen well, and can explain complex ideas without disappearing into jargon (essential).
• You’re resilient and persistent - if the first approach doesn’t work, you try another (essential).
• You’re organised, manage your time well, and can juggle multiple moving parts (essential).
• You enjoy working as part of a team and actively contribute ideas, feedback, and solutions (essential).
• You care about quality - validating assumptions, checking data, and producing work you’re proud to put your name to (essential).