Strategist, Data & Analytics

Accountabilities

• • Lead current-state data assessments and develop phased analytics roadmaps that connect client data capabilities to measurable marketing objectives.
  • Design KPI frameworks, segmentation strategies, measurement approaches, and advanced testing programs that support customer engagement and marketing performance.
  • Develop practical predictive models using Python and applied machine learning, selecting analytical approaches based on each client’s data maturity and business needs.
  • Translate predictive insights into personalization, audience activation, and other actionable marketing strategies.
  • Architect semantic layers, data contracts, and documentation that enable AI agents and LLMs to safely and accurately interact with marketing data.
  • Develop evaluation frameworks, human-in-the-loop controls, and guardrails for agentic workflows, assessing retrieval quality, tool selection, reliability, and output safety.
  • Design agentic workflow specifications showing how autonomous or semi-autonomous systems can use predictions, audience segments, and customer insights to support personalized marketing execution.
  • Develop scalable data strategies and collaborate with internal engineering teams, agency partners, and client technology teams to translate business requirements into production-ready data models and marketing data marts.
  • Advise clients on practical AI adoption, including model and technology evaluation and foundational governance covering data quality, explainability, compliance, and responsible use.
  • Act as a trusted data and analytics advisor across client engagements, connecting technical implementation with strategic marketing priorities.
  • Translate complex analytical findings and technical concepts into clear, compelling presentations for marketing leaders and executive stakeholders.
  • Support business development and account expansion through technical scoping, effort estimation, solution design, and pitch development.
  • Turn successful client solutions into repeatable frameworks, templates, methodologies, and internal intellectual property.

  Requirements

  • 5–8+ years of progressive experience in data, analytics, or data science, with significant experience applying these disciplines to marketing, CRM, customer analytics, or digital personalization.
  • Bachelor’s or Master’s degree in Business Analytics, Data Science, Management Analytics, or another quantitative discipline.
  • Strong hands-on proficiency with Python, SQL, and applied machine learning techniques, with the ability to select appropriate quantitative approaches for different business problems.
  • Practical experience with modern cloud data environments such as Snowflake, Databricks, or equivalent platforms, including identity resolution, data mart architecture, and reverse ETL or activation schemas.
  • Familiarity with AI/ML frameworks and responsible AI governance concepts, including data quality, explainability, compliance, and ethical considerations.
  • Experience in an agency or management consulting environment is strongly preferred, particularly experience managing multiple client workstreams in a dynamic setting.
  • Strong communication and presentation skills, with the ability to translate technical implementations and analytical findings into strategic, outcome-oriented narratives.
  • Ability to operate as both a practitioner and advisor, moving comfortably between developing data logic and presenting strategic recommendations to senior marketing leaders.
  • Strong problem-solving and analytical abilities, with the capacity to bring structure to ambiguous client challenges and develop practical paths forward.
  • A scalable mindset, with experience creating reusable frameworks, templates, methodologies, and solutions rather than one-off deliverables.
  • Curiosity and a forward-looking approach to modern data technologies, AI, and evolving industry practices.
  • Practical understanding of AI limitations and governance, with the ability to distinguish valuable agentic applications from technology hype.
  • Experience with semantic-layer readiness, tool-calling schemas, agentic workflow orchestration, or AI evaluation frameworks (Evals) is a strong plus.
  • Must have current authorization to work in the United States; relocation assistance is not available.

  Benefits

  • Competitive annual salary of $120,000–$140,000, depending on skills, education, experience, certifications, and scope of responsibilities.
  • Flexible remote work environment.
  • Medical, dental, and vision coverage.
  • Short-term and long-term disability insurance.
  • Life and AD&D insurance.
  • Flexible Paid Time Off.
  • Additional ancillary benefits and employee perks.
  • Collaborative culture that values diverse perspectives, innovative thinking, and practical problem solving.
  • Opportunity to work on complex, high-impact data and AI initiatives for leading organizations.
  • Meaningful exposure to the intersection of marketing, data, technology, and emerging AI capabilities.