Director, Data Strategy and AI

Octagon

4h•$110,000 - $130,000•Hybrid

About The Position

STRATEGY / Lead cross-functional data and AI initiatives that strengthen Octagon’s client analytics programs and accelerate internal adoption of practical AI-enabled workflows — partnering closely with technical specialists and business stakeholders to deliver measurable outcomes. Our headquarters are in Stamford, CT, but the location of this position can be flexible with priority given to candidates open to hybrid work (3 days week in office) in one of our office locations - - Stamford, CT, New York, NY, Charlotte, NC, Atlanta, GA, Chicago, IL, Los Angeles, CA, and Miami, FL. We will also consider a remote-based working arrangement for qualified candidates. You are a pragmatic, collaborative leader who can translate between technical teams and business stakeholders. Your mission is to drive alignment, prioritize the right work, and create the conditions for a small, high-agency team to deliver great client analytics and internal AI-enabled tools. You will own the planning and execution of key data and AI initiatives, represent the work credibly with senior stakeholders, and help remove blockers across functions — without needing to be the person who writes every line of code or builds every system yourself.

Requirements

6+ years in data analytics, data strategy, product operations, or a related function — with experience leading cross-functional work and delivering analytics or data products in a client- or stakeholder-facing environment
Strong analytical fluency (e.g., SQL and/or R/Python) with the ability to work effectively with engineers and analysts; you don’t need to be the primary builder of pipelines, but you should be able to ask great questions and evaluate tradeoffs
Demonstrated ability to set priorities, manage dependencies, and drive execution across multiple teams; prior people management is a plus but not required
Understanding of the AI product lifecycle (prototype to production) and what production-grade deployment involves, with the ability to speak credibly about prompt engineering, agent development, and evaluation frameworks at a strategic level (hands-on experience is a plus)
Comfort working in a modern data/AI stack (cloud, APIs, basic security concepts) and partnering with technical owners on decisions; familiarity with AWS/Linux/Posit (or equivalents) is helpful but not required
Excellent communication and stakeholder management skills — able to represent technical work clearly and credibly, build trust across functions, and create space for specialists to own their domains
Ability to navigate governance and compliance constraints in a complex organization (data access, privacy, vendor/tool approvals) and keep work moving by proactively removing blockers
Familiarity with modern AI/search concepts (embeddings, vector search, retrieval patterns) — enough to partner effectively with engineers and vendors
Exposure to AI agent patterns and multi-step automation workflows (framework experience is a plus, not a requirement)

Nice To Haves

Background in marketing/advertising agencies, sports and entertainment partnerships a major plus
Experience integrating tools into enterprise productivity ecosystems (e.g., Microsoft 365/SharePoint/Teams, Power Platform, Google Workspace) is a plus
Background in sponsorship, sports marketing, or media measurement — including familiarity with audience data, brand tracking, social listening, and campaign performance datasets
Familiarity with how production data/AI systems are operated (monitoring, reliability, release processes) and how teams reduce risk while shipping quickly

Responsibilities

Lead the data strategy for major brand partners including sponsorship measurement, investment analysis, and performance reporting across complex, multi-platform programs
Serve as the senior data point of contact in client-facing engagements — translating analytical findings into actionable sponsorship strategy for CMOs, brand strategists, and senior marketing stakeholders
Design and own the measurement infrastructure for each client program: data structures, KPI frameworks, reporting systems, and automation workflows tailored to each brand's existing ecosystem
Support new business development by architecting analytics packages, contributing to RFI and RFP responses, and demonstrating the agency's data capability to prospective clients
Own the roadmap and prioritization of Octagon’s internal AI-enabled tools — aligning stakeholders on the highest-value use cases and ensuring work moves from prototype to production with clear outcomes.
Partner closely with Solutions Engineering and Data Engineering to translate business problems into scoped requirements, clarify dependencies, and drive delivery from discovery through launch.
Establish a lightweight operating cadence (goals, milestones, success metrics) and ensure internal tools drive measurable efficiency and quality gains across account, strategy, partnerships, research, and new business teams.
Stay current on the AI landscape and speak credibly about prompt engineering, agent development, and evaluation at a strategic level — enabling sound build-vs-buy decisions and removing blockers to production-grade deployment.
Partner with engineering to shape the data and AI foundations that support client analytics and internal tools (e.g., pipelines, databases, search/retrieval layers, APIs), with a focus on scalability, reliability, and fit-for-purpose design.
Help coordinate and oversee key analytics environments (e.g., Posit Connect/Workbench or equivalent) and cloud resources in partnership with technical owners, ensuring reliability, security, and appropriate governance.
Ensure the team has the right approach to turning multi-source data (social, media, audience, contract, performance) into analysis-ready models — clarifying requirements, sequencing dependencies, and keeping delivery moving.
Guide data governance expectations (access controls, documentation, observability) in partnership with enterprise teams, balancing compliance requirements with the speed needed to deliver value.
Lead and develop a multidisciplinary team (currently a Senior Analyst, a Solutions Engineer, and a Data Engineer) — setting clear priorities, protecting focus time, and empowering high agency while balancing client delivery and internal product work.
Drive alignment across account, strategy, partnerships, research, and technical teams — translating needs and constraints, unblocking dependencies, and redirecting work when priorities or assumptions change.
Navigate holding-company and enterprise governance (procurement, security, technology standards) — coordinating transitions, clarifying timelines, and advocating for Octagon’s needs without slowing delivery.