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.