Data Science Manager

Harnham; United Kingdom; Remote; GBP 75,000; Full time

Job summary

Join a rapidly growing UK-based start-up as a Data Science Manager. This role offers the chance to lead a talented team in developing cutting-edge KPI prediction models and driving product innovation. With a focus on predictive analytics and KPI tracking, you'll play a crucial role in empowering clients with vital performance insights. This innovative firm is scaling quickly, providing an exciting opportunity for professionals looking to make a significant impact in the data and AI space. If you're passionate about data science and leadership, this is the perfect role for you.

Qualifications

• 5+ years' experience in data science or related field.
• Proven leadership experience in mentoring data scientists.
• Strong grasp of linear regression and statistical modeling.

Responsibilities

• Lead a team of data scientists in building predictive models.
• Oversee data cleaning, feature engineering, and model development.
• Collaborate with leadership to translate business needs into solutions.

Skills

Data Science

Leadership

Linear Regression

Statistical Modeling

SQL

Machine Learning

Web Scraping

Data Processing

Education

Bachelor's degree in a quantitative or technical field

Tools

Docker

Job description

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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.

Base pay range

Direct message the job poster from Harnham

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 level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Analyst, Science, and Engineering

• Industries

  Financial Services and IT Services and IT Consulting

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