Quant Analytics Senior Associate

Join a team where your expertise in analytics and machine learning shapes the future of customer engagement. Experience a culture that values curiosity, collaboration, and growth. 

As a Quant Analytics Senior Associate within Machine Learning Intelligent Operations team, you will play a key role in optimizing Conversational Insights and Insights for Coaching products. Your responsibilities will span the entire problem-solving lifecycle, including: identifying gaps through thorough and inquisitive analyses, conducting root cause analyses using causal inference and machine learning techniques, developing prototype analytics solutions, building and updating business cases, scoping analyses and developing hypotheses, gathering and analyzing complex data, quantifying business value generated through A/B tests or non-randomized pilot, generating actionable insights and delivering presentations to product teams.

Job Responsibilities

• Conduct end-to-end data analysis to improve model performance and operational processes
• Transform complex datasets and automate reporting for business driver analysis
• Identify friction points across customer and specialist interaction channels
• Collaborate with teams to integrate business assumptions and validate hypotheses
• Present clear, actionable insights to peers, leadership, and business partners
• Investigate and resolve issues in data collection, model development, and production
• Develop and document SQL and Python codebases, data dictionaries, and model outputs
• Support agile, digital, or scrum teams in new product development
• Quantify business value generated through experiments and pilots
• Generate and deliver presentations to product teams
• Enable customer self-service across engagement channels

Required Qualifications, Capabilities, and Skills

• Bachelor’s degree in Economics, Data Analytics, Statistics, or a STEM field and 6 years of analytics experience; or Master’s degree in these fields and 2 years of analytics experience
• Hands-on experience with Excel PivotTables, PowerPoint, Tableau, Alteryx, and Python Jupyter Notebook
• Solid programming skills in SQL
• Strong writing and presentation abilities
• Strong understanding of multi-linear regression, logistic regression, clustering, classification techniques including LightGBM and XGBoost, controlled experiments, and causal inference methods
• Professional experience with AWS, Spark/EMR, ChatGPT, Confluence, and Snowflake
• Proficient in big data ETL processes for structured and unstructured databases
• Excellent communication skills for developing and delivering concise presentations
• Detail-oriented problem solver with a track record of meeting tight deadlines
• Collaborative team player with curiosity and ability to operate independently

Preferred Qualifications, Capabilities, and Skills

• Extensive experience in consumer banking operations, servicing, collections, or marketing
• Trained in multivariate statistics, regression analysis, Python, SQL, and visualization tools
• Experience with machine learning, natural language processing, and large language models
• Good understanding of IT processes and databases, with ability to work directly with data owners and custodians