Machine Learning Operations Team - Quant Analytics Senior Associate

Job Responsibilities

• Conduct end‑to‑end data analysis to enhance LLM and GenAI model performance across both AWS and on‑premises environments.
• Transform complex datasets, automate reporting, and perform business driver analysis to improve operational processes and applications. Utilize advanced methods to identify customer and specialist friction points across multiple interaction channels.
• Collaborate with cross‑functional teams to integrate business assumptions with production data, validate hypotheses, and identify production flaws.
• Create and present clear, actionable insights to peers, executive leadership, and business partners.
• Proactively investigate and resolve issues in data collection, model development, and production phases.
• Develop SQL and Python codebases, and document data dictionaries and model outputs in a clear and concise manner.
• Serve as a member of agile, digital, or scrum teams, providing data and analytics support for new product development.

• Bachelor's degree in Economics, Data Analytics, Statistics, or a STEM related field; or Master’s degree in the same fields with at least 2 years of professional analytics experience.
• Solid programming skills in SQL.
• Hands‑on experience with Excel Pivot Tables, PowerPoint presentations, and data wrangling and visualization tools including Tableau, Alteryx, and Python Jupyter Notebook.
• Training in multivariate statistics, regression analysis, Python, SQL and visualization tools including Tableau.
• Professional experience with AWS, Spark/EMR, ChatGPT, Confluence, and Snowflake.
• Strong understanding of multivariate regression, logistic regression, clustering, classification techniques including LightGBM and XGBoost, controlled experiments, and causal inference methods (DD, PM, NN).
• Experience with Machine Learning, Natural Language Processing (NLP), and large language models (LLM).

• Extensive experience in consumer banking units such as operations, servicing, collections, or marketing.
• Proficiency in big data ETL processes for both structured and unstructured databases.
• Good understanding of IT processes and databases, with the ability to work directly with data owners and custodians, contributing to the development of analytics data hubs.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy, or disability.

We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.