Strategist, Data & Analytics

Shift Paradigm

$120K — $140K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-8+ years of experience in data, analytics, or data science focused on marketing and personalization
  • Bachelor's or Master's degree in Business Analytics, Data Science, or related field
  • Hands-on proficiency in Python, SQL, and applied ML techniques
  • Experience with modern cloud data environments, including identity resolution and data mart design
  • Familiarity with AI/ML frameworks and responsible governance practices
  • Experience in an agency or consultancy setting managing client interactions
  • Strong communication skills with the ability to convey complex technical information clearly

Responsibilities

  • Lead data assessments and design analytics roadmaps for clients
  • Develop KPI frameworks, segmentation models, and testing strategies for marketing outcomes
  • Design predictive models and evaluate data maturity to inform client strategies
  • Architect semantic layers and data contracts for AI agents
  • Collaborate with data engineers to build scalable data strategies
  • Advise clients on AI adoption and create foundational governance frameworks
  • Support business development by drafting technical scopes and creating internal templates

Benefits

  • Remote work flexibility
  • Collaborative culture promoting diverse perspectives and innovative thinking
  • Opportunities to make a measurable impact for clients
  • Comprehensive medical, dental, and vision coverage
  • Flexible paid time off and ancillary benefits
Full Job Description
The Role

As a Strategist, Insights & Analytics, you act as the connective tissue between business goals, data architecture, and analytical execution across client engagements. You specialize in turning complex customer data into actionable marketing solutions, designing data models, predictive analytics frameworks, measurement strategies, and the semantic foundations required for AI agents to query customer data safely.

You are equal parts practitioner and advisor: comfortable collaborating directly with client engineering teams to define data logic, while translating complex analytical findings into compelling narratives that marketing leaders can act on. Working alongside cross-functional team members-engineers, analysts, and project leads-you bring big-firm data science depth to real-world marketing challenges in a lean, agile environment. You stay on the cutting edge of modern cloud data platforms, predictive modeling, and AI capability, bringing fresh perspectives to client accounts before they ask for them.

What You'll Accomplish

  • Marketing Analytics Strategy & Measurement: Lead current-state data assessments and design phased analytics roadmaps for client engagements. Develop robust KPI frameworks, segmentation models, and advanced testing strategies that drive measurable marketing outcomes.
  • Applied Analytics & Predictive Modeling: Design practical predictive models using Python and applied machine learning techniques. Evaluate data maturity to select the right analytical approach for each client, turning model outputs into targeted personalization and activation strategies.
  • Agentic Enablement: Architect semantic layers (such as Genie Ontology, dbt semantic layers, or Unity Catalog documentation) and tool-calling data contracts that enable AI agents and LLMs to accurately query marketing data marts without hallucinating. Develop realistic evaluation frameworks (Evals) and human-in-the-loop guardrails for agentic workflows, testing agent retrieval quality, tool selection accuracy, and output safety in marketing execution. Design agentic workflow specs for marketing operations - mapping how autonomous or semi-autonomous agents can consume churn predictions, creative affinity tags, or audience segments to draft or trigger personalized campaigns.
  • Data Architecture & Engineering: Architect scalable data strategies and collaborate with data engineering talent-whether in-house, agency partners, or client IT teams-to ensure solutions are built to spec. You will translate business logic into production-ready data models and marketing data marts that hold up against the realities of fragmented, real-world client data.
  • AI Strategy & Responsible Governance: Help clients navigate fit-for-purpose AI adoption by evaluating models/tools and drafting foundational AI governance frameworks covering data quality, explainability, compliance, and ethics.
  • Strategic Advisory & Client Leadership: Serve as a trusted subject matter expert on client accounts, bridging technical build conversations and strategic marketing reviews. Translate complex data outputs into clear, executive-ready presentations.
  • Business Development & Practice Assets: Support account expansion and pitch efforts by drafting technical scopes, estimating level of effort, and designing solution frameworks. Help turn custom client deliverables into repeatable internal templates and firm IP.


What You Bring

Experience & Expertise

  • 5-8+ years of progressive experience in data, analytics, or data science, with strong depth applied directly to marketing, CRM, or digital personalization challenges.
  • Bachelor's or Master's degree in Business Analytics, Data Science, Management Analytics, or a related quantitative field.
  • Hands-on proficiency with Python, SQL, and applied ML techniques; comfortable evaluating the right quantitative approach for a given business problem.
  • Practical experience working in modern cloud data environments (Snowflake, Databricks, or equivalent), including identity resolution, data mart design, and reverse ETL/activation schemas.
  • Familiarity with AI/ML frameworks and responsible AI governance principles.
  • Agency or management consultancy experience strongly preferred-you thrive in dynamic, client-facing environments managing multiple workstreams.
  • Excellent communicator skilled at translating technical builds into strategic, outcome-oriented narratives.
  • Huge plus if you have experience around semantic layer readiness, tool-calling schema design, agentic workflow orchestration, and evaluation frameworks (Evals).

Mindset

  • Practitioner & Advisor: Equally comfortable writing data logic specs for an engineering team as you are presenting strategic insights to a CMO.
  • Thrives in Ambiguity: Able to step into unstructured client problems, filter out noise, and chart a concrete, actionable path forward.
  • Builds for Scalability: Thinks in terms of repeatable frameworks, templates, and reusable assets rather than isolated one-off deliverables.
  • Forward-Looking: Treats modern data technology and AI as moving targets, actively staying current on industry trends.
  • Grounded AI Realist: Distills the hype around autonomous agents into practical, governed use cases; understands that great agentic execution depends on clean metadata, strict context maps, and clear data boundaries.

What We Offer

  • Competitive compensation aligned with your experience and impact
  • Remote flexibility
  • Collaborative culture that values diverse perspectives and innovative thinking
  • Work that makes a measurable difference for your clients

Comp & Benefits

The salary range for this role is $120,000 to $140,000. Salary is based on several factors including but not limited to skillset, relevant education, level of experience, certifications, and scope of responsibilities.

In addition to base salary, SH/FT offers benefits such as medical, dental, vision, STD/LTD, Life/AD&D, Flexible Paid Time Off, and various other ancillary benefits and perks.

No relocation assistance can be offered at this time.

All inquiries are held in strict confidence.

The pay range for this role is:

120,000 - 140,000 USD per year (Remote (United States))

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