Data Scientist - Banking

🔒 Confidential Employer
Posted 23 April 2026
LOCATION
Sheffield
TYPE
Contract
LEVEL
Mid-Senior level
CATEGORY
Finance
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Python SQL Machine Learning (ML) Natural Language Processing (NLP) credit risk fraud detection risk management

FULL DESCRIPTION

Job details

: Posted 16 April 2026 : LocationSheffield : Job type [Contract](/jobs/contract-1) : Discipline [Commodities and Financial Services](/jobs/commodities-and-financial-services)

Job description

​The Role: Data Scientist - Banking

Location: Sheffield, UK

Position Type: Contract Inside IR35

Remote work option Available: Hybrid – 2 Days Onsite

Job Description:

A Data Scientist with banking experience designs predictive models, analyses financial data, and develops ML/NLP solutions for risk management, fraud detection, and customer analytics. Key responsibilities include building credit risk scorecards, automating data pipelines, and ensuring regulatory compliance, typically requiring 3–5+ years of experience with Python, SQL, and statistical modeling in financial institutions.

Key Responsibilities

  • Predictive Modeling & Analytics: Develop behavioural segments, credit risk scorecards, and predictive models for customer onboarding, cross-selling, and churn retention.
  • Fraud & Risk Management: Utilise advanced analytics to identify anomalies and fraudulent activities in transaction data. Implement risk models (probability of default) and maintain regulatory compliance.
  • Data Handling: Extract, clean, and analyze structured and unstructured data from internal/external sources.
  • Technology & Tools: Write advanced SQL queries and Python/R scripts for data manipulation and build machine learning algorithms (e.g., Scikit-learn, TensorFlow).
  • Stakeholder Communication: Translate complex analytical findings into actionable business insights for management.

Required Experience & Skills

  • Domain Expertise: 3+ years of experience in banking or financial services, specifically in credit risk, fraud strategy, or compliance.
  • Technical Skills: Proficiency in Python, R, SQL, and big data technologies (Spark/Hadoop).
  • Modeling Capabilities: Hands-on experience with Machine Learning (ML), Natural Language Processing (NLP), or Large Language Models (LLMs).
  • Education: Master’s degree in Statistics, Econometrics, Mathematics, Finance, or Data Science.
  • Soft Skills: Strong analytical mindset, detail-oriented approach, and the ability to work under pressure.

If this opportunity is of interest, apply now!

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