Data Strategy & Growth Manager

Fusion92•Chicago, IL

11d

About The Position

The Data Strategy & Growth Manager connects Data Science & Strategy (DSS) with internal departments and external clients. The role identifies opportunities to apply data across the organization and helps translate data strategies into high-quality, timely, impactful execution. Reporting to the SVP, Strategy – Data Science & Technology, the manager works closely with the VP Data Strategy and cross-functional leaders to understand business and client needs, identify value-creating uses for consumer data, and bring relevant strategies, products, and capabilities into discussions. The role helps teams understand available data and how DSS can support objectives across client strategy, marketing services, new business, and product development. This consultative position combines data strategy, cross-functional influence, internal enablement, client engagement, and execution leadership. It serves as a connection point between business stakeholders and the Data Science execution team, helping ensure initiatives are well scoped, inputs and data are available, expectations and timelines are aligned, and deliverables are accurate, relevant, well-presented, and fit for purpose. The role may manage additional Strategist and/or Project Manager resources as the team scales.

Requirements

At least 5 years of experience in data strategy, consulting, client services, business development, marketing strategy, or a related role involving cross-functional influence and solution development.
Experience with third-party aggregated data sources, such as Experian or Acxiom.
Strong understanding of applying data and analytics to marketing, media, customer, and business use cases, including combining first-party client data with third-party marketing data.
Strong consultative and relationship-building skills, including the ability to influence stakeholders without deep data or analytics expertise.
Excellent communication, presentation, and storytelling skills, with the ability to explain complex data capabilities as clear business value.
Commercial mindset and ability to identify opportunities, build internal demand for data capabilities, and contribute to new business and account growth.
Proven ability to work across departments and influence without direct authority.
Experience working with data science, analytics, technology, or data product teams, and sufficient technical fluency to discuss segmentation, modeling, data enrichment, identity, audiences, and data activation.
Strong strategic thinking and problem-solving skills, including the ability to turn an ambiguous business problem into a clear data opportunity and path forward.
Background in data, marketing, media, data services, consulting, technology, or a related environment.

Responsibilities

Identify opportunities for data, analytics, and data products to create value for clients and internal teams.
Build relationships across departments such as Marketing Services, Client Services, and Sales, advising them on how data can support their objectives.
Promote relevant data capabilities, ideas, and use cases, and increase adoption of DSS capabilities and data assets.
Translate business needs into data strategies and connect teams with appropriate data, products, capabilities, and resources.
Develop presentations, examples, case studies, and materials that make data capabilities accessible to non-technical teams.
Expand use of existing data assets, products, and solutions across clients, teams, and use cases.
Partner with client-facing teams to identify data opportunities for client strategies, pitches, proposals, and engagements.
Participate in client and prospect conversations, understand business challenges, and translate them into potential data solutions.
Collaborate with Data Science leadership to shape solutions that are strategically valuable, commercially viable, and feasible to deliver.
Explain the business value of data capabilities clearly to clients and identify opportunities to expand existing client relationships.
Partner with the Data Science execution team to align initiatives with business and client objectives and support successful delivery.
Translate business and client requirements into clear scope, priorities, assumptions, timelines, and expected deliverables.
Ensure data, access, inputs, documentation, and other execution requirements are available, and proactively resolve gaps or dependencies.
Maintain visibility into the DSS execution pipeline and address risks, ambiguities, quality concerns, and delivery challenges.
Review data science outputs for accuracy, relevance, appropriate presentation, and alignment with stakeholder expectations.
Help establish consistent standards for scoping, quality-checking, communicating, and delivering DSS work, and improve the connection between strategy and execution.
Develop repeatable frameworks and playbooks to help teams incorporate data into client strategy, new business, and cross-functional initiatives.
Track adoption and impact of data capabilities and identify ways to increase utilization and value.
Align priorities, expectations, and communication between DSS and cross-functional stakeholders throughout initiatives.
As the team scales, manage additional Strategist and/or Project Manager resources supporting data strategy, enablement, and execution.