This position will be involved in a diverse range of activities supporting client’s Commercial Analytics functions. This position will be imbedded in the Structure and Fundamentals team and will focus on enhanced data driven solutions in support of team’s activities. While our focus is for AI expertise, this role will support a much broader range of data science activities and provides meaningful exposure to and engagement in Commercial Analytics work product. Responsibilities • Collect, clean, and preprocess large datasets to ensure high-quality data for quantitative analysis including AI applications. • Develop and implement machine learning models for predictive analytics, recommendation systems, anomaly detection, and other AI-driven insights. Implement solutions that improve efficiency of team activities. • Analyze and interpret complex data structures to derive meaningful business insights. Collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to integrate AI solutions into group workflows. Optimize and fine-tune AI models to enhance accuracy, efficiency, and scalability. • Stay up to date with the latest advancements in AI, machine learning, and data science technologies. • Create data visualizations and dashboards to communicate findings to stakeholders effectively. Document methodologies, processes, and findings to maintain transparency and reproducibility. Qualifications • Bachelor's degree, Master's degree preferred, in data science, computer science, quantitative finance, statistics, or mathematics 3+ years of work experience in data analysis, machine learning, and AI applications High level of proficiency in SQL and quantitative programming (Python, R, MATLAB). • Experienced in dealing with large data sets. Experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-Learn. Strong knowledge of data visualization tools such as Tableau, Power BI, or Matplotlib. • Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. Strong communication skills. Ability to translate complex data into actionable insights. • The ability to manage multiple tasks independently and deadlines in a fast-paced environment. • Ability to proactively seek new ideas and solutions to improve the status quo. Strong work ethic – reliable and accountable. Ability to work cooperatively with all levels of staff as part of a team. A commitment to the highest ethical standards and to act with professionalism and integrity. Preferred Qualifications: Experience with Natural Language Processing (NLP) or Computer Vision. Knowledge of big data technologies such as Spark, Hadoop, or Databricks. Exposure to deep learning techniques and neural networks. Understanding of MLOps principles and deployment of AI models in production environments.