Data Scientist

Role Title:Data Scientist

Location: London, UK (Hybrid – 3 days onsite per week)

Contract Duration: 6 Months

Role Overview

We are seeking an experienced Data Scientist to join a high-profile programme delivering advanced AI and Machine Learning solutions. You will work closely with an established delivery team to develop, validate, deploy, and support production-grade machine learning models and associated services.

The ideal candidate will have strong hands-on experience in Python-based data science, machine learning model development, and deployment of AI solutions into production environments.

Key Responsibilities

• Design, develop, and implement AI/ML-based solutions.
• Build, validate, and deploy production-ready machine learning models.
• Perform data analysis, feature engineering, and model optimisation.
• Collaborate with data scientists, engineers, and business stakeholders to solve complex business challenges.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and risk indicators.
• Troubleshoot, debug, and improve existing code and models.
• Maintain reproducible and collaborative workflows using version control tools.
• Contribute to model monitoring, performance evaluation, and continuous improvement activities.

Required Skills & Experience

• 3–5 years of Data Science and Machine Learning experience.
• Strong hands-on experience with Python, including:
• Pandas
• NumPy
• Scikit-Learn
• Strong SQL skills for querying and analysing structured datasets.
• Experience developing and validating machine learning models, including:
• Classification Models
• Unsupervised Learning
• Outlier/Anomaly Detection
• Ranking Models
• Experience with feature engineering and data preparation.
• Experience deploying machine learning solutions in production environments.
• Familiarity with containerised deployment approaches and tools such as:
• SageMaker
• Podman
• Docker
• Similar deployment platforms
• Experience with Git and version control best practices.
• Experience performing Time-Series Analysis and trend identification.
• Strong Exploratory Data Analysis (EDA) capabilities.

Desirable Skills

• Model Explainability tools such as SHAP or LIME.
• Model Monitoring and Drift Detection.
• Experience within Risk, Fraud, Financial Crime, Regulatory Technology, or Compliance-focused environments.
• Experience with Record Linkage and Entity Resolution solutions.
• Knowledge of Network Analytics and Graph Analytics.
• Experience with graph databases and technologies such as:
• Neo4j
• Amazon Neptune
• Cypher
• Gremlin
• Understanding of ensemble and rank aggregation techniques such as Robust Rank Fusion (RRF).

Preferred Candidate Profile

• Strong analytical and problem-solving mindset.
• Excellent communication and stakeholder engagement skills.
• Experience working within Agile delivery environments.
• Ability to work independently while collaborating effectively within a wider delivery team.
• Passion for AI, Machine Learning, and data-driven decision making.