The Senior Data Scientist will drive the end-to-end development, maintenance, and governance of analytical models to support Anti-Financial Crime (AFC) initiatives. This role involves collaborating with stakeholders, ensuring model performance, and embedding strong governance practices while working with structured and unstructured data.
Key Responsibilities:
New Model Development
- Collaborate with model end-users, Head of AFC Analytics, Business Analysts, and Data Engineers to identify areas for new model development and include them in the pipeline.
- Develop model narratives including purpose, logic, parameters, data requirements, and output structure.
- Undertake end-to-end AFC model development including data wrangling, exploratory analysis, feature selection, model selection, training, and testing.
- Build a range of models (rule-based, supervised/unsupervised) using structured, semi-structured, or unstructured data.
Model Maintenance
- Incorporate business feedback into model updates.
- Re-train and recalibrate models periodically to prevent model drift.
Model Governance
- Support enhancements to existing model governance policies and processes.
- Participate in model governance activities including testing, bias assessment, and ensuring compliance with ethics standards.
Skills / Qualifications
- Bachelor's degree in Data Science, Statistics, Finance, or a related field; Master's degree or relevant certifications are a plus.
- Minimum 6 years of experience with advanced analytical models and machine learning applications.
- Experience in AML/AFC analytics and financial crime compliance.
- Proficient in SQL, Python, R, SAS; experienced with big data tools (Hive, Spark, Impala).
- Familiarity with NLP, network link analysis, and distributed databases.
- Prior experience with large-scale analytics projects.
- Strong analytical, problem-solving, and decision-making skills.
- Ability to manage multiple priorities and work under pressure.