Data Science Strategist

Develop marketing measurement strategies, dashboards, data pipelines, attribution analyses, and media mix models. Partner with clients and internal teams to translate business questions into KPIs and actionable recommendations. Build automated data tools, QA processes, and reporting solutions using BI platforms, Python or R, SQL, and marketing data sources. Evaluate AI-assisted tools and support responsible adoption while managing multiple client projects. The summary above was generated by AI Data Science StrategistAbout the RoleWe’re looking for a Data Science Strategist who is equally comfortable in a client discovery call and deep in a data pipeline. You’ll sit on the Data Science team within Integrated Marketing, where your days will be primarily hands-on and technical: building dashboards, connecting data sources and running measurement models. Just as important, you’ll bring a strategist’s ear. You’ll listen to the business problem behind a data request, figure out what’s really being asked, and design creative, practical solutions using the right combination of tools. This role blends data strategy and data building. If you enjoy turning a messy marketing question into a clean measurement framework, and then building the thing yourself, this is for you.What You’ll DoData strategy & problem solving

• Partner with account, media, social, SEO and client teams to understand their goals and translate business questions into clear measurement plans and KPIs.
• Diagnose data problems (gaps in tracking, disconnected sources, conflicting numbers) and recommend creative solutions across our toolset.
• Design measurement frameworks for integrated campaigns spanning paid, owned and earned channels.
• Present findings and recommendations to internal stakeholders and clients in plain, actionable language.

Dashboards, data tools & AI-assisted building

• Build, automate and maintain client and internal dashboards and reporting solutions.
• Use NinjaCat (and other BI and data-connector tools) to unify cross-channel marketing data into scalable reporting.
• Build custom data tools beyond dashboards, such as automated data pipelines, calculators, audit and QA scripts, reporting templates and lightweight internal apps that make the team faster.
• Explore and pilot new AI-powered features in our BI and martech stack, and help shape how the team uses AI responsibly in its data work.
• Develop data models and QA processes that keep reporting accurate, consistent and trustworthy.

Attribution & marketing measurement

• Develop and run multi-touch attribution (MTA) analyses to understand channel contribution across the customer journey.
• Build and interpret media mix models (MMM), working across a range of toolsets (e.g., open-source frameworks such as Meridian or Robyn, platform-native tools, or custom models in Python/R).
• Recommend budget allocation and optimization strategies based on attribution and MMM outputs, including incrementality and testing approaches where appropriate.

Innovation

• Stay current on martech, privacy changes, AI and measurement methods, and bring new ideas and tools to the team.

• 4-7+ years of experience in marketing analytics, data science, or business intelligence, ideally in an agency or consultancy environment.
• Strong digital marketing background: a working understanding of paid search, paid social, programmatic, SEO, email and web analytics.
• Proven dashboard building and BI experience (e.g., NinjaCat, Looker Studio, Power BI, Tableau).
• Experience building other data tools and automations, not just dashboards (e.g., scripts, pipelines, templates or small apps).
• Comfortable using AI tools as part of your building workflow (coding, analysis, automation and documentation), with the judgment to check and validate what they produce.
• Hands-on expertise with Google Analytics 4 and Google Tag Manager.
• Experience building or applying multi-touch attribution and media mix modeling, using more than one toolset or methodology.
• Strategic mindset: you listen first, ask good questions and connect data work to business outcomes.
• Excellent communication skills and the ability to explain technical concepts to non-technical audiences.
• Comfortable managing multiple client projects and deadlines at once.

Highly preferred

• Experience with NinjaCat.
• SQL proficiency and experience with Python or R for analysis and modeling.
• Experience with cloud data warehouses (e.g., BigQuery, Snowflake)
• Familiarity with privacy and consent frameworks (consent mode, server-side tagging, first-party data strategies).
• Experience in regulated industries such as healthcare.

CompensationThe expected salary range for this role is $85,000 - $110,000. Final compensation will depend on experience, skills and location.Where You’ll WorkAnywhere in the U.S. We’re a remote-first workplace with optional in-office days in Boston, Chicago, Detroit, Los Angeles, Nashville, New York, Portland, Washington DC, and more Why Join FINN Partners?

• Competitive salary, health, dental, and vision insurance
• 401(k)
• Generous PTO policy, plus paid holidays
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Please upload your resume and cover letter, as well as indicate your desired salary in $US Dollars. While we appreciate the interest of all candidates, we will only respond to those with whom we have a greater interest. About FINN Partners: Founded in 2011 on the core principles of innovation and collaborative partnership, FINN Partners has become one of the fastest growing independent public relations agencies in the world. With 1,300 professionals globally, FINN provides clients with access and capabilities in North America, Europe and Asia. FINN Partners clients are also supported through longstanding partner agencies via its membership in the PROI network of leading agencies around the world. Headquartered in New York, FINN Partners operates in 39 locations: Abu Dhabi, Atlanta, Bangalore, Bangkok, Beijing, Boston, Chicago, Columbus (Ohio), Delhi, Denver, Detroit, Dublin, Fort Lauderdale, Frankfurt, Hong Kong, Honolulu, Jerusalem, Kuala Lumpur, London, Los Angeles, Madison (Wisc.), Manila, Melbourne, Minneapolis, Mumbai, Munich, Nashville, Orange County (Calif.), Paris, Portland (Ore.), San Diego, San Francisco, Seattle, Shanghai, Singapore, Sydney, Washington D.C. and Yangon.