Help improve how customers experience service across voice and digital channels. In this role, you’ll turn complex data into insights that inform product and operational decisions. You’ll collaborate with partners across servicing, product, finance, marketing, and analytics to identify opportunities and measure impact. If you enjoy structured problem-solving, storytelling with data, and delivering results in an agile environment, this role offers meaningful visibility and growth.
As an Associate, Voice Product Analytics within the Consumer and Community Banking Data and Analytics organization, you will support advanced analytics work across Operations functions, channels, and products. You will contribute across the analytics lifecycle, including scoping, data lineage documentation, data development, hypothesis development, analysis, and insight generation. You will help teams understand customer journeys and friction points across voice and digital interactions. You will develop clear, executive-ready narratives and materials that help stakeholders prioritize actions that improve customer experience and operational outcomes.
You will use enterprise data—spanning customer, account, digital, telephony, financial, and operational sources—to help build automated and repeatable analytics solutions. You’ll work in an agile delivery model to iterate, incorporate feedback, and deliver incremental value. You will partner closely with cross-functional teams across servicing and product organizations to align on success measures, test approaches, and performance tracking.
Job Responsibilities
- Partner with Operations stakeholders and product groups to understand business drivers, processes, and underlying data
- Support initiatives that improve customer experience and help reduce operating expenses across Operations product groups
- Help scope analytics work by clarifying problem statements, hypotheses, success metrics, and approach
- Document data lineage and contribute to data development to enable accurate, reusable analyses
- Analyze customer interactions across channels (calls, branch, online, and mobile) to identify journey patterns and friction points
- Develop and report performance metrics and key performance indicators (KPIs); apply methods such as trend analysis and segmentation to inform improvements
- Contribute to business cases by sizing opportunities and quantifying expected benefits and tradeoffs
- Support test and pilot design by defining populations, measurement approach, and evaluation criteria; analyze outcomes and recommend next actions
- Build dashboards and visualizations to measure impact and enable self-service performance monitoring
- Prepare and deliver presentations that summarize insights, conclusions, and recommended actions for stakeholders
Required Qualifications, Capabilities, and Skills
- Minimum of 3 years of experience in analytics, strategy, or a related quantitative role
- Bachelor’s degree in a quantitative field (or equivalent practical experience)
- Experience delivering analytics solutions using an agile methodology (Scrum and/or Kanban)
- Strong SQL skills and hands-on experience using at least one analytics language (Python or R)
- Experience with data visualization and dashboarding (for example, Tableau)
- Experience working with large datasets and analytics environments (for example, relational databases and/or Spark/Hive)
- Ability to translate ambiguous questions into structured analyses, measurable outcomes, and clear recommendations
- Strong communication and stakeholder management skills, including comfort presenting to senior leaders
- Experience with analytics workflow tools (For example: Alteryx)
Preferred Qualifications, Capabilities, and Skills
- Graduate degree in a quantitative or related field
- Experience using Agentic AI Tools (Github, Copilot, Cortex AI
- Familiarity with Amazon Web Services (AWS) and cloud-based data solutions
- Familiarity with data mining, statistical modeling, machine learning, and other advanced analytics methods
- Experience writing code and automating processes to source, transform, and analyze data from multiple sources (including unstructured data)
