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American Express · 1 day ago

Senior Manager, Small Business Card & Rewards Analytics

New York, NY

Full-time

Hybrid

Senior Level

$123K/yr - $215K/yr

American Express is a leading global payment company committed to innovation and customer service. The Senior Manager, Small Business Card and Rewards Analytics will lead analytics efforts to enhance card product performance, engagement, and customer relationships by leveraging advanced analytical techniques and collaborating with various teams.

Credit CardsFinanceFinancial ServicesPaymentsTravel

Comp. & Benefits

No H1B

Responsibilities

Translate business problems into data strategies and lead analytical workstreams on SBS customer engagement, usage, and retention leveraging advanced analytical techniques including clustering, machine learning, and statistical analysis

Lead strategy and execution for creation of SBS card transaction and customer data assets including migration of source data to cloud environment and design of sustainable, optimized data structure

Analyze expected impact on business of potential charge product features and enhancements and advise senior leaders on product roadmap

Design, launch and measure tests of product construct configurations to increase rewards and benefits awareness, redemption, and spend; Build analytical frameworks for robust measurement when clear A/B testing doesn’t exist

Identify and build behavior-based segmentation to provide insights into customer behavior and drive recommendations for business priorities

Serve as subject matter expert for SBS card portfolio performance, leading regular product performance reviews for card leadership

Manage and prioritize demands for data, ad hoc analytics, and reporting from multiple stakeholders, reallocating resources as necessary to ensure alignment with business priorities

Qualification

Data analyticsPredictive modelingCloud-based toolsStatistical analysisSQLPythonMachine learningData visualizationCuriosityCommunication skillsTeam collaborationLeadership

Required

Relevant professional experience including extensive experience in hands-on analytical role(s) leveraging data to drive decisions, translate operational performance into financial implications, and influencing business strategies

Extensive experience building sustainable data assets using cloud-based analytical tools, querying languages, and visualization software (e.g., SQL, Python, Databricks, Tableau)

Good understanding of card economics and performance drivers with proven success in driving business results via strategic analysis. Experience in Charge/Loyalty analytics is a plus

Excellent written and verbal communication skills with the ability to explain technical concepts and analytics-driven findings to non-technical stakeholders, and to explain business processes, concepts, and issues to technical resources

Team player with proven ability to influence and collaborate with others across all levels of an organization

Strong curiosity and initiative in tackling complex business analysis; dives deeply into the data, relentlessly pursues its meaning, and how these insights can drive business performance

Proven track record effectively managing priorities across multiple senior level keyholders and influencing stakeholders across all levels of organization

Proven track record translating business problems into data strategies and solutions, leading complex, multi-stage analytical workstreams, and advising senior leadership on data-based insights

Proven ability to lead and develop team of product analysts, providing leadership and coaching to the team in areas such as application of advanced analytical concepts, sustainable data models, and effective presentation

Bachelor's degree preferably in a quantitative field (e.g. statistics, engineering, math, science, economics, etc.)

Preferred

Relevant professional experience in hands-on analytical role(s) leveraging data to drive decisions, translate operational performance into financial implications, and influence business strategies; Financial services experiences is a plus

Expertise in data science and advanced analytical techniques including clustering, machine learning, and statistical analysis