Data Science Manager

Harnham
Luton
8 months ago
Applications closed

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Data Science Manager – Property Tech – London

Data Science Manager - Property Tech - London

Data Science Manager – Property Tech – London

Manager, Data Science

Data Science and Analytics Manager

Data Analytics Manager

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 inpredictive analyticsandKPI trackingacross 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 aData 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’ experiencein data science or a closely related field.
  • Proven leadership experience — mentoring or managing junior data scientists.
  • Expert Python programming skills (essential).
  • 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.

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