Principal Associate, Data Scientist - Applied AI

Responsibilities: Partner with a cross-functional team of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions for customers. Use a broad technology stack including Python, LangChain, AWS, Workflows, and Vector Databases to design Multi-Agent systems and advanced RAG pipelines over large volumes of numeric and textual data. Build Generative AI models and pipelines across the full lifecycle, including context engineering, fine-tuning, evaluation, validation, and deployment. Apply interpersonal skills to translate technical work into clear business goals.

Requirements: Currently has, or is in the process of obtaining (with expectation of completion on or before scheduled start date), a Bachelor’s Degree in a quantitative field plus 5 years of experience performing data analytics. Currently has, or is in the process of obtaining (with expectation of completion on or before scheduled start date), a Master’s Degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics. Currently has, or is in the process of obtaining (with expectation of completion on or before scheduled start date), a PhD in a quantitative field. At least 2 years of experience in AI, Information Retrieval, Deep Learning, or NLP. At least 3 years of experience in Python, Scala, or R. At least 3 years of experience with machine learning. At least 3 years of experience with SQL. Experience with clustering, classification, sentiment analysis, time series, and deep learning. Built models with validation and backtesting; can interpret a confusion matrix or ROC curve. Technologies Python LangChain AWS Workflows Vector Databases Team Description The Commercial Bank Applied AI team embeds Generative AI directly into core business processes. Focus areas include enterprise-grade architectures using Multi-Agent Systems, Advanced RAG, Context Engineering, and Tool-Calling Frameworks. Ideal candidates have hands-on experience in machine learning and AI from professional industry work or rigorous academic research.

Ideal Candidate: Innovative: researches and evaluates emerging technologies; stays current on state-of-the-art methods and applications. Creative: brings definition to large, undefined problems; shares new ideas and drives toward answers. Technical: comfortable with open-source languages; develops data science solutions using open-source tools and cloud computing platforms. Statistically-minded: understands model validation and backtesting; interprets confusion matrices and ROC curves; has experience across clustering, classification, sentiment analysis, time series, and deep learning.

Preferred Qualifications: Master’s Degree in a STEM field plus 3 years of experience in data analytics, or a PhD in a STEM field. At least 2 years of experience in AI, Information Retrieval, Deep Learning, or NLP. At least 3 years of experience in Python, Scala, or R. At least 3 years of experience with machine learning. At least 3 years of experience with SQL.Location and Employment

Location: New York, NY (onsite)

Type: Full-time

Experience: Minimum 5 years