Selby Jennings
AI/ML Data Scientist
About the Role
A tier-1 global investment bank is seeking a highly skilled and AI/ML Data Scientist to join their innovative front office team. You will work collaboratively with data scientists, engineers, and software engineers to leverage cutting edge AI and analytics tools.
Key Responsibilities
Leverage advanced AI and Machine Learning research methods to develop new tools and analytics for the business. Utilize the latest advancements in AI and Large Language Model (LLM) research to solve complex capital markets challenges. Apply a range of analytical techniques-from traditional statistical methods to state-of-the-art machine learning-to extract insights from diverse and complex datasets. Develop scalable, production-grade ML systems and ensure robust deployment in real-world financial applications. Communicate findings effectively through compelling storytelling, visualizations, and presentations tailored to both technical and non-technical stakeholders. Required Qualifications
PhD in Computer Science, Machine Learning, Physics, or a related STEM field. 6+ years of hands-on experience in developing and deploying machine learning or AI systems in production environments in financial services. Proficiency in Python and essential libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch, PySpark). Solid foundation in software engineering best practices, including modular code design, version control, and documentation. Excellent communication and collaboration skills, with the ability to work across multidisciplinary teams.
About the Role
A tier-1 global investment bank is seeking a highly skilled and AI/ML Data Scientist to join their innovative front office team. You will work collaboratively with data scientists, engineers, and software engineers to leverage cutting edge AI and analytics tools.
Key Responsibilities
Leverage advanced AI and Machine Learning research methods to develop new tools and analytics for the business. Utilize the latest advancements in AI and Large Language Model (LLM) research to solve complex capital markets challenges. Apply a range of analytical techniques-from traditional statistical methods to state-of-the-art machine learning-to extract insights from diverse and complex datasets. Develop scalable, production-grade ML systems and ensure robust deployment in real-world financial applications. Communicate findings effectively through compelling storytelling, visualizations, and presentations tailored to both technical and non-technical stakeholders. Required Qualifications
PhD in Computer Science, Machine Learning, Physics, or a related STEM field. 6+ years of hands-on experience in developing and deploying machine learning or AI systems in production environments in financial services. Proficiency in Python and essential libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch, PySpark). Solid foundation in software engineering best practices, including modular code design, version control, and documentation. Excellent communication and collaboration skills, with the ability to work across multidisciplinary teams.