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Intuit's Consumer Group (CG), a team serving the needs of over 30+ million US consumers to file their annual tax returns, is looking for a Principal Marketing Manager, Media Investment Intelligent Decisioning.

This role sits at the center of how TurboTax makes investment decisions. You will own the partnership between Paid Media, Data Science, and Finance that determines channel mix and investment allocation across the TurboTax envelope, and you will run the weekly SLT Investment Review that translates model output and marketplace signal into a clear point of view for senior leadership. In parallel, you will help build the Central Decision Engine — the architecture that unifies MMM, platform, and creative signal into a single, always-on source of investment guidance — moving the team from weekly reporting to real-time, model-driven decisioning.

This is both a strategic and a builder's role. You will need to be equally comfortable defending an investment recommendation in front of the SLT and contributing to the data architecture that produces it. The Principal Marketing Manager will report to the Director of Paid Media.

What You'll Bring

Strategic, Analytically Grounded Communicator

• Ability to translate complex model output — MMM curves, channel mix tradeoffs, marginal ROI — into a clear, channel level direction and executive-ready narrative, both written and verbal

• Comfortable owning and driving a recurring analytics and finance forum, a channel reporting and guidance forum and a senior leadership forum. This includes setting the agenda, anticipating questions, and proposing / defending a strategic recommendation.

• Strong point of view, backed by data — someone who forms and influences a recommendation

Cross-Functional Influence

• Proven ability to build durable, high-trust partnerships with Data Science and Finance — functions with different incentives and different definitions of "right" — and align them to a shared investment view

• Skilled at managing up and across a matrixed organization without formal authority over the teams you depend on

• Able to represent Paid Media's interests in cross-functional forums and instilling confidence

Integrated Media & Budget Management Fluency

• Deep working knowledge of an integrated media environment spanning search, programmatic/digital media, social, video, streaming, and above-the-line channels, and how investment shifts in one channel affect performance in another

• Experience managing a large media investment envelope: forecasting, in-season reallocation, marginal curve analysis, and defending spend decisions with data

• Understands how agency partners (search, digital media, ATL) operationalize a channel mix decision once it's made

Builder's Mindset

• Excited by the opportunity to help design and build a system, in an evolving AI led evolving media enviorment

• Comfortable in ambiguity — defining architecture and process where none currently exists, in close partnership with Paid Media and GTM leadership

Responsibilities

Investment Decisioning & Data Science / Finance Partnership

• Own the operating partnership with Data Science and Finance on investment decisions and channel mix — translating MMM output, incrementality findings, and marketplace signal into a shared point of view on where dollars should go

• Serve as the connective tissue between the quantitative model and the media strategy — ensuring model recommendations account for real-world channel, creative, and seasonal dynamics

• Build and maintain the recurring cadence, documentation, and decision log that governs how investment decisions get made and revisited across the fiscal year

• Partner with Finance on forecast accuracy, in-season reallocation, and the tradeoffs between committed and flexible spend

Weekly Investment Reviews with team and SLT

• Own and drive the weekly SLT Investment Review — setting the agenda, structuring the narrative, and presenting channel-level and envelope-level performance, risks, and recommendations to senior leadership

• Lead with the so-what: distill dense model output and channel results into a small number of clear, decision-ready recommendations

• Track and communicate key investment metrics (ITPY, mROI, impression share) across channels and escalate risks or opportunities in season

• Build trust with SLT as a credible, consistent voice on where the business stands and what to do about it

Central Decision Engine & Intelligent Decision Architecture

• Partner with the Measurement & Intelligent Decision Architecture team to build the Central Decision Engine — the unified layer that synthesizes MMM, platform data, incrementality, and attribution into a single investment decision source

• Support the architecture that flows Recast outputs, DMA-level modeling, and channel-level performance signals into one actionable interface, replacing our current reporting and decision structure

• Work with Data Innovation and Analytics teams to ensure the underlying data infrastructure can support always-on, model-driven guidance

• Contribute to the standards and documentation that make the Central Decision Engine durable and scalable for our 1-3 vision

• Help connect the Intelligent Decisioning focus area to adjacent FY27 workstreams (data signal architecture, creative decisioning, AI channel operations)

Channel Mix & Integrated Media Management

• Bring a channel mix recommendation from model output to executable plan — working across search, digital media, Comms and ATL team and agency partners to translate a decision into media execution

• Monitor marginal ROI and impression share by channel, flagging over- or under-investment and proposing reallocation

• Understand and account for cross-channel effects (e.g., ATL halo on search, streaming/video contribution to full-funnel performance) in every mix recommendation

Operational Excellence & Continuous Improvement

• Continuously refine the investment decisioning process — reducing time from signal to decision and from decision to execution

• Stay current on MMM, measurement, and marketing-AI developments and bring an informed point of view on when and how to evolve the decisioning architecture

• Document decisions, assumptions, and model changes so the Central Decision Engine remains auditable and defensible over time

Qualifications

• 7–10 years in paid media investment strategy, marketing analytics, or a related quantitative marketing role, ideally in a high-investment, performance-oriented environment

• Demonstrated experience partnering with Data Science and/or Finance functions on investment or resource allocation decisions

• Direct experience with marketing mix modeling (MMM) — and comfort translating model output into a business recommendation

• Track record of owning and presenting to senior leadership on a recurring basis; strong executive presence and the ability to defend a recommendation under questioning

• Working knowledge of an integrated media environment: search, programmatic/digital, social, video/streaming, and above-the-line, and how they interact

• Experience managing or directly influencing a large media investment envelope, including forecasting and in-season reallocation

• Comfort working with data infrastructure teams (Databricks or equivalent) to define architecture requirements, even without being a hands-on engineer

• Strong prioritization and organization skills necessary to lead cross-functional and cross-agency initiatives in a highly matrixed, fast-moving environment

• BA/BS degree required

• Minimal travel for industry networking, media, and related events

• Hybrid Role: 2–3 days in office/week

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.