<p>About the Opportunity</p><p>We&#39;re seeking a Data Scientist who thrives at the intersection of business strategy, marketing analytics, and statistical analysis. This role sits between a traditional Data Analyst and Data Scientist, focusing less on reporting and more on answering complex business questions that influence marketing investment decisions.</p><p>You&#39;ll join a high-performing analytics team responsible for evaluating and optimizing one of the organization&#39;s largest performance marketing channels. The ideal candidate brings a strong background in B2C marketing analytics, paid search, experimentation, and statistical analysis, with the ability to translate ambiguous business problems into actionable recommendations.</p><p><br></p><p>What You&#39;ll Do</p><p>In this role, you&#39;ll use data to influence marketing strategy and investment decisions across large-scale paid search programs.</p><p><strong>Key Responsibilities:</strong></p><ul><li>Design and execute incrementality tests, holdout experiments, and pre/post analyses to measure the true business impact of paid search investments.</li><li>Build statistical frameworks to evaluate campaign performance and guide strategic decision-making.</li><li>Analyze large datasets using SQL and Python to uncover trends, performance drivers, and opportunities.</li><li>Develop recommendations regarding marketing spend allocation through ROI and marginal return analyses.</li><li>Translate complex business questions into structured analytical approaches and defensible recommendations.</li><li>Partner with marketing, analytics, and business stakeholders to influence investment and optimization strategies.</li><li>Create and maintain trusted reporting, dashboards, and performance measurement frameworks.</li><li>Validate findings, quality-check reporting, and challenge assumptions to ensure analytical rigor.</li><li>Support ad hoc analyses including:</li><li>Marketing budget optimization</li><li>Competitive performance analysis</li><li>Search engine algorithm impact assessments</li><li>Customer acquisition and conversion performance studies</li></ul><p>What a Typical Month Looks Like</p><ul><li><strong>50%</strong> Ongoing performance management and campaign optimization</li><li><strong>30%</strong> Strategic projects, experimentation, and deep-dive analysis</li><li><strong>20%</strong> Team collaboration, stakeholder meetings, and team development</li></ul>

<p>Required Qualifications</p><ul><li>3+ years of experience in Marketing Analytics, Media Analytics, Business Analytics, or a similar data-rich environment.</li><li>Experience supporting B2C marketing organizations.</li><li>Advanced SQL skills with experience querying and analyzing large datasets.</li><li>Strong statistical background, including:</li><li>Hypothesis testing</li><li>Statistical significance testing</li><li>Power analysis</li><li>Experimental design</li><li>Experience translating ambiguous business questions into actionable recommendations.</li><li>Proficiency with Python (Pandas preferred) for data analysis.</li><li>Experience building reports and dashboards using Tableau, Looker, or similar BI platforms.</li><li>Bachelor&#39;s degree in Statistics, Economics, Mathematics, Marketing Analytics, Data Science, or a related quantitative field.</li></ul><p>Preferred Qualifications</p><ul><li>Hands-on experience with paid search platforms such as:</li><li>Google Ads</li><li>Microsoft Ads</li><li>Search Ads 360 (SA360)</li><li>Experience with one or more of the following:</li><li>Incrementality Testing</li><li>Media Mix Modeling (MMM)</li><li>Multi-Touch Attribution (MTA)</li><li>Experience using AI or GenAI tools to improve analytical workflows, reporting, or research.</li><li>Experience working in consumer-focused digital marketing environments.</li></ul><p>What Makes Someone Successful in This Role</p><p>We&#39;re looking for someone who:</p><ul><li>Thinks like a strategist, not just a report builder.</li><li>Can explain complex analyses to both technical and non-technical audiences.</li><li>Enjoys solving ambiguous business problems with data.</li><li>Challenges assumptions and validates findings before making recommendations.</li><li>Collaborates effectively across marketing, analytics, and leadership teams.</li><li>Is comfortable influencing decisions without directly owning budgets.</li></ul>

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