Data Scientist Jobs

Experts who transform raw data into actionable insights. A core role in the data-driven decision-making process of modern organisations.

Open roles
33
Salary range
£42k – £150k
Hiring companies
23

Data Scientists are the linchpins of data-driven organisations, transforming vast amounts of raw data into meaningful insights that inform strategic decisions. They work across a range of industries, from finance and healthcare to retail and technology, using statistical models, machine learning, and data visualisation to uncover patterns and trends. Whether in a startup or a large corporation, Data Scientists play a crucial role in driving innovation and optimising business performance.

What the role does

Inside the role of a Data Scientist

A typical week for a Data Scientist is a mix of data exploration, model building, and stakeholder communication.

  1. 01
    Analyse large datasets to identify patterns and trends.
  2. 02
    Develop and validate statistical models and algorithms.
  3. 03
    Collaborate with cross-functional teams to understand business needs.
  4. 04
    Present findings and recommendations to stakeholders.
  5. 05
    Document and maintain data pipelines and models.
  6. 06
    Stay updated with the latest research and tools in data science.
Salary on the board

£42k – £150k

Based on advertised midpoints across the 34 priced listings posted in the last 12 months. Base salary only.

By seniority
£k base
Entry
42
45
1 job
Mid
45
150
14 jobs
Senior
60
120
12 jobs
Lead
67
125
5 jobs
Skills & tools

What hiring managers ask for

% of 8 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

Machine Learning
75%
Python
75%
Data Science
63%
Pandas
50%
PyTorch
38%
A/B Testing
25%
Experimentation
25%
AWS
25%
Docker
25%
NLP
25%
SQL
25%
Cross-Functional Collaboration
25%
Career ladder

From Junior to Principal

A typical UK progression for data scientists. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior Data Scientist

    0–2 yrs

    Assist in data collection and cleaning, and support more senior team members in model development and analysis.

  2. Level 2

    Data Scientist

    2–5 yrs

    Own specific projects, develop and validate models, and communicate insights to stakeholders.

  3. Level 3

    Senior Data Scientist

    5–8 yrs

    Lead complex projects, mentor junior team members, and influence strategic decisions with data-driven insights.

  4. Level 4

    Principal Data Scientist

    8+ yrs

    Drive the overall data strategy, lead a team of data scientists, and collaborate with C-level executives.

Pathway

How to become a Data Scientist

There's no single route, but most people follow some version of these steps.

  1. 1

    Acquire foundational skills

    Gain a strong understanding of statistics, programming, and data manipulation. Complete relevant courses or a degree in a quantitative field.

  2. 2

    Build a portfolio

    Work on personal or open-source projects to build a portfolio that showcases your data science skills and expertise.

  3. 3

    Gain practical experience

    Secure internships or entry-level roles to gain hands-on experience in a professional setting. Learn to work with real-world data and business challenges.

  4. 4

    Specialise in a domain

    Choose a specific industry or domain, such as healthcare or finance, and deepen your knowledge and skills in that area.

  5. 5

    Lead projects and teams

    Take on leadership roles, manage projects, and mentor junior team members. Develop your communication and management skills.

  6. 6

    Influence strategic decisions

    Collaborate with C-level executives to drive the organisation's data strategy. Influence key business decisions with data-driven insights.

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FAQs

Common questions

  • Essential skills include strong statistical knowledge, programming proficiency (Python, R), data manipulation, and communication skills.

  • Gain relevant skills through courses or a degree, build a portfolio, and seek internships or entry-level roles to gain practical experience.

  • The typical progression is from Junior Data Scientist to Data Scientist, Senior Data Scientist, and finally Principal Data Scientist.

  • Key responsibilities include data analysis, model development, stakeholder communication, and staying updated with the latest research and tools.

  • Salaries vary based on experience and location. For more detailed salary information, please refer to the salary section on this page.

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