Join the team that is a key contributor in measuring and optimizing the ecosystem of customer-initiated activities that connects customer signals to banker interactions and business outcomes.
As a Data Scientist Senior Associate, within the Customer Journey and Experimentation Team, you will focus on answering questions such as: what types of customer-initiated activities are driving the most value, how can we measure and optimize the performance of handraisers across channels, and how do we lay the groundwork for customer journey analysis and multi-touch attribution to prioritize our bankers' time effectively.
Job Responsibilities:
- Analyze the performance and value of customer activities to understand what customers are doing and the downstream business impact.
- Develop measurement frameworks and lay the analytical groundwork for customer journey analysis and multi-touch attribution by mapping touchpoints and building pipelines that connect customer signals to banker interactions and outcomes
- Support the development of data-driven strategies to help bankers focus their time on the highest-value customer interactions, analyzing patterns in customer-initiated activity to identify which customer signals are most predictive of meaningful engagement and conversion.
- Apply strong programming skills to extract, integrate, and transform data from diverse sources into cohesive analytical solutions that enable rigorous, data-driven decision-making
- Deliver clear, well-structured analyses, ad-hoc reporting, and presentations that translate technical findings into intuitive business language for senior stakeholders
Required Qualifications, Capabilities, and Skills:
- Bachelor's degree with 3+ years of experience in an analytics, data science, or business intelligence role, with demonstrated ability to work end-to-end from data extraction through insight delivery.
- Strong SQL skills with experience writing complex queries to pull, transform, and summarize large datasets across relational databases (Teradata experience preferred)
- Exposure to measurement and testing methodologies (e.g., A/B testing, incrementality measurement, test/learn frameworks) and familiarity with modern data platforms including Hadoop, AWS, or Snowflake
- Proficiency in Python for data manipulation, analysis, and automation
- High standards for work quality with meticulous attention to detail, ensuring accuracy and rigor across all analytical outputs and deliverables.
- Strong business intuition — demonstrated ability to think beyond raw data and understand the underlying business context, with a focus on practically solving real business problems
- Effective communication skills — ability to relay findings clearly and concisely to senior stakeholders and cross-functional partners from a variety of business functions, translating business requests into analytical strategies
- Experience with data visualization tools such as Tableau or similar platforms for building clean, actionable dashboards
Preferred Qualifications, Capabilities, and Skills:
- Knowledge of customer journey analytics, multi-touch attribution, or marketing analytics concepts.
- Interest in or experience with statistical and machine learning techniques and their practical business applications
- PySpark experience is a plus
- Financial services experience is a plus, but not required