Responsibilities

• Client‑Centric - Create and lead the analytics strategy for an account by learning the client’s business, understanding their media strategy, and developing annual learning agendas, incrementality testing roadmaps, and strategic analysis plans. - Act as the leading analytics voice on your accounts, helping clients and internal teams focus on the highest-value questions and measurement priorities. - Build productive working relationships with clients so you can provide a consultative approach to insights development and make impactful recommendations, especially as it relates to translating complex MMM outputs into strategic business decisions – clearly explaining what the model results mean, what they don't mean, and delivering the actionable "so what" behind the numbers. - Anticipate the attribution methods needed to comprehensively measure full-funnel media, across various attribution systems (e.g., Last-Touch, MMM), tie results back to business-driving outcomes, and assess current tactics plus channel expansion opportunities. - Listen actively for client-health signals, identify high-value growth opportunities, and lead the appropriate escalation or recommendation path. - Demystify advanced statistical concepts for non-technical executives, translating algorithmic outputs into clear business narratives and strategic recommendations. Product‑Led - Use BI tools, dashboards, Bliss Point applications, and analytics environments to support insight generation, recommendation development, and strategic client storytelling. - Maintain advanced fluency in reporting environments, data tools, and analytics workflows so you can improve the quality, speed, and strategic usefulness of outputs. - Identify novel tools, data sources, and methodologies that can elevate analytical impact and improve how insight is delivered to clients. - Help translate technical outputs, data structures, and measurement limitations into language clients and account teams can understand and act on. - Contribute feedback on workflow, tooling, and insight-delivery improvements that strengthen Tinuiti’s broader analytics capability. Data & Measurement‑Driven - Lead execution of quantitative methods, including forecasting, A/B testing, incrementality testing, regression analytics, segmentation, and campaign evaluation. - Lead end-to-end delivery of complex analytical projects, from scoping and hypothesis generation through execution, synthesis, and presentation of results. - Connect data across channels, reports, and methodologies to generate integrated insights that guide optimization, investment, and growth decisions. - Leverage a strong technical foundation in Media Mix Models to formulate actionable budget optimization tests and identify knowledge gaps where incrementality testing is required to validate channel results. - Maintain strong quality-control standards across analyses, reporting, and visualization to ensure outputs are accurate, actionable, and decision-useful. - Use SQL and related analytical tools as practical working tools for extracting, validating, and interpreting structured marketing data. - Recommend analytical approaches that balance business need, rigor, and timeliness rather than defaulting to either simplistic reporting or unnecessary complexity. The Tinuiti Way - Maintain a holistic understanding of how channels, measurement, and business goals fit together so analytics work supports broader strategy, not just isolated reporting. - Partner tightly with Media, Client Strategy, and Analytics counterparts to ensure analytical outputs feed back into planning, optimization, and investment choices. - Stay current on experimentation, attribution, forecasting, analytics technology, and performance measurement practices, and apply that knowledge to improve client strategy. - Bring a strong point of view on how insights from tests and MMM read outs should inform business and marketing decisions, not just summarize results. - Help connect analytics work to broader Tinuiti capabilities and integrated ways of working, reinforcing stronger cross-functional problem-solving. Owner Mindset - Take accountability for the client’s analytics strategy, analytical output quality, and the usefulness of recommendations delivered across your account scope. - Turn broad, messy, or ambiguous client questions into clear analytical approaches with practical next steps. - Prioritize effectively across clients, partner relationships, and internal initiatives, focusing effort on the highest-impact analytical work. - Identify cross-sell signals, emerging business needs, and strategic growth opportunities through your understanding of client priorities and unmet analytics questions. - Contribute to stronger team standards by improving workflows, analytical rigor, and how insight is translated into action. Ways of working and values - Greatness attracts Greatness: Raise the craft bar, seek feedback, and stay open to stronger tools, methods, and ways of thinking. - Clients grow, we grow: Anchor analytics work in business outcomes, decision quality, and measurable impact. - Culture of ownership: Be accurate, proactive, and accountable; improve continuously and help others do the same. Professional & Technical Qualifications - Experience: 7–10 years of experience in analytics-focused roles, with a strong track record of analytics strategy development, client relationship building, consultative insight development, Media Mix Model familiarity, and quantitative methods. - Analytics strategy: Demonstrated experience building annual learning agendas, testing roadmaps, and strategic analytical approaches tied to client and business needs. - Client leadership: Ability to lead an account-level analytics practice for a business or group of businesses, anticipate analytics needs, and independently answer high-value questions. - Ambiguity handling: Must be able to take broad or ambiguous questions and topics and produce a clear, finite approach to address them. - BI fluency: Advanced skills in business intelligence platforms such as Tableau, Power BI, Metric, or similar tools. - AI fluency: Comfort using AI tools to improve efficiency, quality, and day-to-day decision-making, with strong judgment in validating outputs and handling sensitive data. - Data environment fluency: Strong familiarity with cloud data environments such as Snowflake, Redshift, or similar tools. - SQL: Advanced working fluency in SQL for querying, validating, and analyzing structured marketing data. - Quantitative methods: In-depth experience with statistical analysis and predictive methods; strong experience with R and/or Python for testing, forecasting, modeling, and advanced analytical work. - Communication: Excellent communication and interpersonal skills, with confidence preparing decks and presenting to senior client leadership. - Execution: Advanced Excel / Google Sheets and PowerPoint / Google Slides skills; strong ability to multitask, prioritize, and manage time effectively across clients, partner relationships, and internal initiatives.
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Requirements

• Experience: 7–10 years of experience in analytics-focused roles, with a strong track record of analytics strategy development, client relationship building, consultative insight development, Media Mix Model familiarity, and quantitative methods.
• Analytics strategy: Demonstrated experience building annual learning agendas, testing roadmaps, and strategic analytical approaches tied to client and business needs.
• Client leadership: Ability to lead an account-level analytics practice for a business or group of businesses, anticipate analytics needs, and independently answer high-value questions.
• Ambiguity handling: Must be able to take broad or ambiguous questions and topics and produce a clear, finite approach to address them.
• BI fluency: Advanced skills in business intelligence platforms such as Tableau, Power BI, Metric, or similar tools.
• AI fluency: Comfort using AI tools to improve efficiency, quality, and day-to-day decision-making, with strong judgment in validating outputs and handling sensitive data.
• Data environment fluency: Strong familiarity with cloud data environments such as Snowflake, Redshift, or similar tools.
• SQL: Advanced working fluency in SQL for querying, validating, and analyzing structured marketing data.
• Quantitative methods: In-depth experience with statistical analysis and predictive methods; strong experience with R and/or Python for testing, forecasting, modeling, and advanced analytical work.
• Communication: Excellent communication and interpersonal skills, with confidence preparing decks and presenting to senior client leadership.

Benefits

• Unlimited PTO: At Tinuiti, we believe you deserve time to rest, recharge, and enjoy life unplugged. When you prioritize time for yourself, you're able to bring your best self to work. That’s why we offer unlimited paid time off, a fully remote environment, and flexibility to take the time you need, when you need it. On top of that, we provide 20 paid holidays, including multiple long weekends, to ensure you have dedicated time to step away and disconnect. We're proud to offer above-industry standard work-life balance, consistently rated as one of the most loved benefits by Tinuitians year after year.
• Healthcare: Medical, Dental, Vision, Life & Disability, Flex Spending Accounts
• Retirement: Match up to 4% of your contributions at 100%
• Perks and Wellness: Fringe, Forma, Unlimited Telemedicine and Teletherapy available at no cost, Thankful giving, Equity
• Parental Leave: Birthing parents receive 16 weeks of leave with 100% pay (partners 12 weeks) after the birth or adoption of a child.
• Learning and Development: On-demand learning, mentorship program, leadership and management development programs and resources