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Data Science Manager

Harnham
united kingdom
11 months ago
Applications closed

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18 Jun 2025 (11 months ago)
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This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

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Building Data Science and Machine Learning Teams in the UK | The Talent Driving The Data and AI Revolution

Data Science Manager

Remote (UK-Based)

Up to £75,000

The Company

This UK-based start-up has achieved rapid growth in just two years, now boasting a team of ~40 people across divisions. Following a successful funding round and with a strong pipeline ahead, they continue to scale at pace.

They specialise in predictive analytics and KPI tracking across a broad range of companies and industries. Their predictive insights empower hedge funds and investors with critical performance data, ahead of public earnings reports.

The Role

As a Data Science Manager, you’ll take ownership of the end-to-end development of KPI prediction models and manage a team of data scientists, helping refine their workflows and ensure high-quality deliverables.

You will:

  • Lead and mentor a team of data scientists in building predictive models.
  • Oversee data cleaning, feature engineering, and model development pipelines.
  • Build and maintain robust, scalable linear regression and statistical models for KPI forecasting.
  • Drive improvements in internal tooling and API integrations.
  • Collaborate closely with leadership, engineering, and the revenue team to translate business needs into data science solutions.
  • Play a key role in product innovation, helping shape how new data products are designed and delivered.

What They're Looking For

  • 5+ years’ experience in data science or a closely related field.
  • Proven leadership experience — mentoring or managing junior data scientists.
  • Strong grasp of linear regression, statistical modeling, and data processing best practices.
  • Proficient in SQL (MySQL preferred).
  • Experience with web scraping, machine learning techniques, and dashboarding tools is a bonus.
  • Familiarity with Docker, time series forecasting, or LLM technologies is advantageous.
  • A background or exposure to finance is useful but not mandatory.
  • Bachelor’s degree (or higher) in a quantitative or technical field.
  • Strong coding samples (e.g., GitHub projects).
  • Practical experience building production-level models and data pipelines.
  • Ability to bridge data science and product development goals.

If this role looks it could be of interest, please reach out to Joseph Gregory, or apply here.

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionAnalyst, Science, and Engineering
  • IndustriesFinancial Services and IT Services and IT Consulting

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