Data Scientist

About the Role

The ideal applicant thrives on learning and working with data at scale with agility. This role involves collaborating closely with teams to extract meaningful insights from complex datasets, formulating precise questions, and delivering accurate answers. You will develop impactful visualizations to convey intricate findings effectively to non-technical audiences, shaping decision-making and steering strategic efforts across the organisation.

Responsibilities

• Leverage statistical approaches and machine learning algorithms to forecast future scenarios and detect new financial crime risks.
• Create predictive models that support risk-focused decisions and prioritise investigation resources.
• Conduct thorough analysis of data quality upstream and within Financial Crime Surveillance (FCS) to ensure data accuracy and completeness.
• Detect and address data quality problems that could undermine the success of financial crime detection initiatives.
• Implement advanced machine learning techniques, including generative AI, Natural Language Processing (NLP), and Large Language Models (LLMs), to enhance pattern recognition and optimize surveillance tactics.
• Design, evaluate, and enhance predictive models that enable real-time monitoring and investigation of financial crimes.
• Utilize advanced programming tools such as Python and R to analyze vast datasets, build algorithms, and execute data-driven solutions, moving beyond reliance on SQL and Excel.

Required Skills and Experience

• At least five years of professional experience in developing and deploying generative models across diverse fields with a successful history of delivering AI-based solutions.
• Solid knowledge of current trends in deep learning, reinforcement learning, and generative modeling techniques, including proven success in building and launching effective applications or solutions.
• Practical experience with natural language processing, computer vision, and related methods such as NLP, LLM, generative AI, OpenAI, Microsoft Cognitive Services (including audio-to-text conversion), text mining NLP, image recognition, and machine learning techniques.
• Strong programming proficiency in Python alongside competent skills in SQL.
• Familiarity with SAS and expertise in PowerBI are considered advantageous.