Senior Associate, Marketing Analytics (Small Business Decision Sciences)
- LocationColumbus, OH, United States
- Work typeNot stated
- EmploymentFull-time
- Posted22 October 2026
- SourceJPMorganChase's careers page (Oracle Recruiting)
Live checkFirst seen 7 days ago; still listed on JPMorganChase's careers page 4 h ago.
Moves fastWhen JPMorganChase takes a role down early, it is usually about 6 days after posting. Apply soon.
At a glance
- Experience3+ years
- EducationBachelor's degree
- Skills and toolsSnowflake, SQL, Python, SAS
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About the role
Be the analytics partner who helps turn marketing investment into measurable, incremental growth. In this role, you’ll shape acquisition campaign decisions from opportunity sizing through test design, execution support, and financial performance measurement. You’ll work closely with Marketing, Modeling, Finance, and Data & Analytics partners to deliver insights leaders can act on. If you’re energized by experimentation, measurement rigor, and clear storytelling, this role offers high visibility and meaningful impact.
Job Summary
As a Senior Associate for Marketing Analytics on the Small Business Decision Sciences team, you’ll deliver analytics across the end-to-end marketing campaign lifecycle, with a focus on acquisition campaigns. You’ll partner with stakeholders to develop business cases, model impact, design tests, support execution, and measure results with financial discipline. You’ll bring a consultative mindset to translate complex data into clear recommendations on audience, offer, channel, and funding decisions. You’ll help strengthen measurement quality through repeatable processes, controls, and well-defined data requirements.
Job Responsibilities
- Lead financial and analytical optimization of marketing programs across opportunity sizing, targeting, test design, execution support, reporting, and insights.
- Own stakeholder relationship management and delivery for assigned marketing partners, including intake, prioritization, scoping, timelines, and outputs aligned to campaign calendars.
- Drive experimentation strategy and measurement rigor, including hypotheses, test/control design, success metrics, and post-test readouts; support execution and measurement feasibility needs.
- Apply predictive models and measurement insights to investment planning and optimization across audience, offer, channel, and funding decisions.
- Build analytic assets and frameworks to evaluate incrementality, profitability, and return on investment (e.g., forecast/proforma vs. actuals; attribution approaches where relevant).
- Leverage and help evolve the analytics toolset, including Snowflake and emerging AI-enabled analytics applications, to improve speed, scale, and consistency.
- Partner across functions (modeling, finance, marketing channels, and delivery teams) to ensure solutions are implementable, controlled, and aligned to standards.
- Define and advocate for data requirements to monitor targeting, execution, and performance; partner with data teams to address gaps, quality, and lineage.
- Maintain and enhance processes and controls that support measurement quality, repeatability, and auditability.
Required Qualifications, Capabilities, and Skills
- 3+ years of related Marketing Data & Analytics experience.
- Master’s degree in a related field, or Bachelor’s degree plus 3+ years of experience in a related discipline.
- Proven hands-on experience delivering financial analytics and performance insights, including campaign test designs, estimation proformas, and actual performance measurement.
- Demonstrated experience with marketing strategy and campaign lifecycle execution.
- Proficiency in analytics languages/tools such as SQL, Python, SAS, or R (or comparable).
- Experience with relational databases and big data platforms, including Snowflake.
- Strong analytical reasoning, interpretive ability, and structured problem solving.
- Technical understanding of data extraction, transformation, and load concepts (ETL/ELT) and how data flows affect analytics outcomes.
- Experience with dynamic, interactive self-serve business intelligence tools (dashboarding and automated reporting).
- Strong written and oral communication skills, including creating executive-ready narratives and presenting complex findings clearly.
- Exceptional collaboration and interpersonal skills, with ability to explain quantitative topics clearly and influence decisions across business and technical partners.
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