The Data Scientist is responsible for the design and development of advanced generative, recommender, and predictive models that will generate value creation.
Requirements
- Heavy MS Azure Data Factory experience is a must.
- Strong and deep knowledge of a broad set of AI methodologies: Generative AI & Agentic AI, deep learning, natural language processing, supervised learning (classification, regression), reinforcement learning
- Proficiency in Python is required together with multiple popular advanced analytics frameworks e.g. pandas, spark, scikit-learn, langchain, langchain, llamaindex, tensorflow, pytorch
- Experience with popular cloud-based ML platforms (AWS SageMaker, Azure Machine Learning) is a plus
- Strong applied understanding of MLOps / LLMOps best practice
- 3+ years of deep applied expertise at developing and deploying complex AI/ML solutions, preferably in a financial services context
Responsibilities
- Lead the design, development, validation, and deployment of innovative, performant, and scalable AI engines, applying rigorous testing to ensure alignment with business objectives.
- Conduct advanced statistical analysis to provide actionable insights, identify trends, and measure performance.
- Apply A/B testing framework to test models' quality and integrate data insights into the business processes.
- Coordinate with different functional teams to implement models, design processes and tools to monitor and analyze model performance and data quality.
- Drive the AI methodology R&D agenda to ensure CLIENT continues to offer added value by best-in-class AI approaches in a fast-moving landscape.
- Thought partner to the Head of AI and Product Manager at identify opportunities to unlock value in the industry by leveraging distinctive AI expertise (machine learning and generative AI) to drive business solutions.
- Experience to merge and transform disparate internal & external data sets together to create inputs for AI
Other
- Openness to working in Agile environments with multiple stakeholders
- Strong communication and collaboration skills to understand business partner needs and deliver solutions
- Professional attitude and service orientation; team player
- Quick learner to business needs and translates them into potential analytics solutions
- Strong analytical and problem-solving skills; healthy skepticism around the validity of data and its biases
