Lead Data Scientist at Tate Nottingham
Nottingham NG1, , United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

08 Nov, 25

Salary

60000.0

Posted On

09 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, Power Bi, Machine Learning, R, Discretion, Sql, Management Skills

Industry

Information Technology/IT

Description

CONFIDENTIAL JOB OPPORTUNITY: LEAD DATA SCIENTIST

Location: Flexible / Hybrid
Contract Type: Permanent
Salary: Competitive, with excellent benefits
We are recruiting a Lead Data Scientist on behalf of a fast-growing financial services organisation. This is an opportunity to join a forward-thinking team focused on driving innovation across the full customer lifecycle using advanced data science and machine learning techniques.

KEY SKILLS & EXPERIENCE:

  • Proven experience delivering end-to-end data science solutions in a commercial environment.
  • Strong technical expertise in predictive modelling, machine learning, and AI.
  • Proficient in R, Python, SQL, and familiar with visualisation tools like Power BI.
  • Excellent problem-solving, communication, and stakeholder management skills.
  • Experience in applying Gen AI tools or techniques is highly desirable.
  • Educated to degree level (2:1 or above) in a numerical discipline.
Responsibilities

ABOUT THE ROLE:

As a Lead Data Scientist, you will play a pivotal role in developing and enhancing data-driven solutions across fraud prevention, marketing strategy, credit risk, and customer management. You’ll have the opportunity to shape the direction of data science initiatives and work with a highly skilled team to implement autonomous decisioning frameworks, predictive modelling, and advanced analytics.

KEY RESPONSIBILITIES:

  • Own and develop predictive models to improve customer outcomes across multiple business domains.
  • Lead model deployment and policy setting to enhance autonomous decisioning.
  • Design and implement test-and-learn strategies that influence key business decisions.
  • Deliver actionable insights through structured analysis and clear communication.
  • Continuously seek and identify opportunities for process improvement through data.
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