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AI Summary

The Data Strategy & Growth Manager acts as a strategic bridge between data science teams and business stakeholders to identify and execute data-driven growth opportunities. This role involves scoping initiatives, ensuring data quality, and translating complex technical capabilities into actionable business value for clients.

Fusion92 is building the future of marketing through an unparalleled, data-driven approach to solving our clients' toughest problems. We call ourselves a Marketing Transformation Partner for clients, as through a culture of curiosity, fearlessness, teamwork and leadership, we turn our expertise toward creating new paths forward where our services and technology together unlock unprecedented growth. 

We’re an independent, national enterprise based in Chicago with hubs in Detroit, Austin and Denver. Fusion92 is committed to a diverse, equitable, inclusive workplace that drives a positive impact in our global community. 

We are experts across every field and discipline in marketing. 

Fusion92 is for those who are obsessed with curiosity and innovation. We unite data scientists, media buyers, copywriters, technologists, developers, consultants, coders, UX/UI specialists, designers, strategists, producers, operations pros and more to deliver real results and to give answers to the unanswerable. 

We launch products, we have patented innovations, we create award-winning ideas — we transform businesses. We are dreamers and doers, and we are ready for you to join us. 

Our difference is our people. That's where you come in. 

If you're curious and looking for a remote-flexible, integrated team where you can fearlessly collaborate and deliver best-in-class work, join us! 


Role Overview 

The Data Strategy & Growth Manager serves as a strategic connector between Data Science & Strategy (DSS), internal departments, and external clients – identifying opportunities to apply data more broadly across the organization while ensuring data strategies are translated into high-quality, timely, and impactful execution. 

Reporting to the SVP, Strategy – Data Science & Technology, this individual will work closely with the VP Data Strategy and cross-functional leaders to understand business and client needs, uncover opportunities where consumer data can create value, and bring the right data strategies, products, and capabilities into those conversations. You’ll help teams across the organization understand what data is available, how it can be leveraged, and how DSS can support their objectives – from client strategy and marketing services to new business and product development – all with the goal of driving stronger client outcomes. The role also serves as a critical connection point between business stakeholders and the Data Science execution team. You’ll help ensure that initiatives are clearly scoped, the right data and inputs are available, expectations and timelines are aligned, and final outputs are accurate, relevant, well-presented, and fit for purpose. 

This is a highly consultative role that combines data strategy, cross-functional influence, internal enablement, client engagement, and execution leadership. The ideal candidate is a strong communicator and relationship-builder with data strategy fluency, a natural ability to uncover opportunities, and the credibility to translate complex data capabilities into clear business value while ensuring those capabilities are delivered effectively. 

What You’ll Do 

Data Strategy, Growth & Internal Enablement 

  • Partner with peers and leaders across the organization to identify where data, analytics, and data products can create new value for clients and internal teams. 
  • Build strong relationships across departments such as Marketing Services, Client Services, and Sales, becoming a trusted advisor on how data can support their objectives. 
  • Proactively bring relevant data capabilities, ideas, and use cases to teams and help increase adoption of DSS capabilities and data assets across the organization. 
  • Translate business needs into clear data strategies and opportunities, connecting teams to the right data, products, capabilities, and resources. 
  • Develop compelling presentations, examples, case studies, and other materials that make data capabilities easy for non-technical teams to understand, sell, and apply. 
  • Identify opportunities to expand the use of existing data assets, products, and solutions across clients, teams, and use cases. 

Client & New Business Strategy 

  • Partner with client-facing teams to identify opportunities where data can strengthen client strategies, pitches, proposals, and ongoing engagements. 
  • Participate in client and prospect conversations to 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. 
  • Help articulate the business value of data capabilities in a clear, compelling, client-friendly way. 
  • Identify opportunities to expand existing client relationships through additional data, analytics, or data product applications. 

Data Strategy Execution & Quality 

  • Partner closely with the Data Science execution team to ensure initiatives are aligned with business and client objectives and set up for successful delivery. 
  • Translate business and client requirements into clear scope, priorities, assumptions, timelines, and expected deliverables for Data Science. 
  • Ensure the team has the data, access, inputs, documentation, and other requirements needed to execute effectively, proactively identifying and resolving gaps or dependencies. 
  • Maintain visibility into the DSS execution pipeline, helping keep work on track and proactively addressing risks, ambiguities, quality concerns, and delivery challenges. 
  • Review data science outputs from a strategic and business perspective to ensure they are accurate, relevant, appropriately presented, and aligned with stakeholder expectations. 
  • Help establish consistent standards for how DSS work is scoped, quality-checked, communicated, and delivered, and continuously identify ways to improve the connection between strategy and execution. 

Leadership & Organizational Enablement 

  • Develop repeatable frameworks and playbooks that make it easier for teams to incorporate data into client strategy, new business, and cross-functional initiatives. 
  • Track adoption and impact of data capabilities across the organization and identify opportunities to increase utilization and value. 
  • Serve as the connective thread between DSS and cross-functional stakeholders, ensuring priorities, expectations, and communication remain aligned throughout an initiative. 
  • As the team scales, manage additional Strategist and/or Project Manager resources supporting data strategy, enablement, and execution. 



Requirements

WHAT YOU’LL BRING 

  • 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 3rd party aggregated data sources (i.e. Experian, Acxiom, etc).  
  • Strong understanding of how data and analytics can be applied across marketing, media, customer, and business use cases, and how 1st party client data can be used with 3rd party marketing data.  
  • Strong consultative and relationship-building skills, with the ability to influence stakeholders who may not have a deep understanding of data or analytics. 
  • Excellent communication, presentation, and storytelling skills – able to translate complex data capabilities into clear business value. 
  • Commercial mindset with the 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 closely with data science, analytics, technology, or data product teams, with enough technical fluency to confidently discuss concepts such as segmentation, modeling, data enrichment, identity, audiences, and data activation. 
  • Strong strategic thinking and problem-solving skills, with the ability to move from an ambiguous business problem to a clear data opportunity and path forward. 
  • Background in data, marketing, media, data services, consulting, technology, or a related environment. 


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