Quant Analytics Senior Associate

You’ll join the Consumer & Community Banking • Data & Analytics team, a strategic partner to the Consumer & Community Banking organization using data and analytics to accelerate growth, improve campaign performance, and deliver actionable insights. In this role, you’ll work closely with stakeholders to enable informed, data-driven decisions and continuous improvement across the Data & Analytics team. As a Quantitative Analytics Senior Associate within the Consumer & Community Banking • Data & Analytics organization, you will leverage your analytical expertise to guide strategic decisions, ongoing reporting, and deep-dive analyses that address emerging business challenges. You’ll collaborate with stakeholders to define goals and develop strategies that drive product performance and enhance user experience. You leverage advanced analytics to inform product development and investment decisions. Job responsibilities Manage and analyze large, complex datasets from multiple sources to develop actionable business strategies and insights that drive measurable outcomesApply advanced analytical and data mining techniques to identify meaningful patterns and correlations within datasets, translating findings into behavioral insights that inform business decisionsCommunicate complex analytical results clearly and effectively to business partners and senior leadership, tailoring presentations to diverse audiences and technical backgroundsConduct sophisticated analysis and deliver tactical and strategic insights using modern visualization and reporting toolsServe as a subject matter expert for data-driven decision-making and opportunity identification, providing guidance on analytical approaches and methodologiesPartner with internal and external clients to solve quantitative business problems, optimize performance, and deliver solutions that address critical business needsAlign with data owners and department managers to contribute to the development of data models, analytics architecture, and enterprise-wide data strategiesIdentify opportunities for process improvement, assess data quality, recognize statistical anomalies, and connect data findings to business processes to enhance operational efficiencyExecute responsibilities with a high degree of autonomy and limited oversight, independently managing programs, refining processes, and engaging stakeholders Required qualifications, capabilities and skills Bachelor’s degree in a quantitative field such as Computer Science, Operations Research, Mathematics, Engineering, Econometrics, Statistics, or related discipline with 6+ years of relevant experienceProficiency in data analysis programming languages such as Python or SAS, with experience in Big Data technologies including Snowflake, Databricks, or equivalent platformsStrong SQL skills and demonstrated experience working with relational databases to extract, manipulate, and analyze dataExceptional interpersonal and collaboration skills with the ability to explain complex mathematical concepts in accessible terms and influence business partners at all levelsProven track record of delivering analytics and insights to multiple levels of management, from operational teams to senior executivesHands-on experience with data mining techniques, analytical methodologies, and translating analysis into business strategy implementation Experience with data visualization techniques and reporting tools such as Tableau, Alteryx, or comparable platforms to create compelling visual narrativesAdvanced analytical, interpretive, and problem-solving skills with the ability to tackle ambiguous business challenges and derive actionable solutionsExcellent written and oral communication skills, with the ability to distill complex analytical findings into clear, concise insights for senior business leaders and non-technical audiencesWork experience in AWS, Spark/EMR, ChatGPT, Confluence and Snowflake. Proficiency in Agile methodologies with tools like Jira or Confluence Preferred qualifications, capabilities and skills Experience in Machine Learning, NLP, and LLM. Experience working with Digital platform and tools like Adobe Analytics is a plus