Data Scientist, Marketing Analytics & Measurement

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    "ExternalDescriptionStr": "<p>The Data Scientist III plays a critical role in designing, developing, and deploying advanced data science and analytics solutions that drive actionable insights and business value. This role applies deep technical expertise and business acumen to solve complex problems, influence decision-making, and improve operational efficiency.</p><p>&nbsp;</p><p>Working on high-impact and often ambiguous initiatives, the Data Scientist III independently leads significant components of projects, mentors junior team members, and proactively identifies opportunities for innovation. This role collaborates cross-functionally with business stakeholders, engineering teams, and leadership to translate data into strategic insights and scalable solutions.</p><p>&nbsp;</p><p>What you’ll be doing:&nbsp;</p><ul style=\"padding-left: 72px;\"><li>Develop and implement advanced marketing measurement solutions, including Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA), to quantify channel performance and optimize spend&nbsp;</li><li>Build and evolve customer lifetime value (CLV) models to inform acquisition, retention, and investment strategies&nbsp;</li><li>Design and deploy personalization and recommendation models to enhance customer engagement and conversion across channels&nbsp;</li><li>Lead experimentation strategy, including A/B and multivariate testing, to evaluate marketing initiatives and product features&nbsp;</li><li>Partner with marketing stakeholders to translate analytical outputs into actionable campaign strategies and optimization plans&nbsp;</li><li>Define and measure incremental impact (lift) of campaigns, promotions, and loyalty programs&nbsp;</li><li>Work with large-scale customer and behavioral datasets to create segmentation frameworks that drive targeted marketing and customer experiences&nbsp;</li><li>Contribute to the development of measurement frameworks across owned, paid, and omnichannel marketing ecosystems</li><li>Collaborate with data engineering and technology teams to ensure scalable and production-ready solutions.</li><li>Develop and maintain reusable data science assets, tools, and frameworks to improve efficiency and consistency.</li><li>Present insights, recommendations, and model outputs to stakeholders, including senior leadership, in a clear and compelling manner</li><li>Serve as a subject matter expert in selected data science domains (e.g., forecasting, customer analytics, pricing, marketing analytics, optimization)</li></ul><p>&nbsp;</p><p>What you bring to the table:&nbsp;</p><ul style=\"padding-left: 72px;\"><li>Strong analytical thinking skills, with the ability to break down complex problems, identify key drivers, and translate findings into actionable insight</li><li>Highly developed problem-solving capabilities, with a proactive approach to identifying challenges and delivering practical, data-driven solutions</li><li>Collaborative mindset with a track record of working effectively across cross-functional teams and building strong, productive relationships</li><li>Ability to adapt quickly in a dynamic environment, balancing multiple priorities and adjusting approaches as business needs evolve</li><li>Demonstrated initiative and ownership, consistently identifying opportunities for improvement and taking action with a sense of urgency and accountability</li><li>Ability to balance statistical rigor with practical business impact in a fast-paced environment</li><li>Excellent communication skills, including the ability to clearly explain complex technical concepts to non-technical stakeholders and tailor messaging to different audiences</li></ul><p>&nbsp;</p><p>What’s needed- Basic Qualifications:&nbsp;</p><ul style=\"padding-left: 72px;\"><li>Bachelor’s Degree in Data Science, Statistics, Computer Science, Engineering, Mathematics or a related field or equivalent work experience.</li><li>5+ years of hands-on experience building and deploying machine learning or statistical models in a business environment</li><li>Strong understanding of statistical methods, including hypothesis testing, regression, and model evaluation techniques</li><li>Experience with marketing analytics use cases such as attribution, campaign measurement, personalization, or customer segmentation</li><li>Hands-on experience with experimentation design and analysis (e.g., A/B testing, uplift modeling)</li><li>Proficiency in Python or R, with demonstrated experience using libraries such as pandas, scikit-learn, TensorFlow, PyTorch, or equivalent</li><li>Experience working with large datasets using SQL (e.g., writing complex queries, optimizing performance)</li><li>Demonstrated ability to independently execute end-to-end data science projects (minimum of 3 completed projects with measurable business impact)</li><li>Experience communicating technical results to non-technical stakeholders (e.g., presentations, dashboards, reports)</li></ul><p>&nbsp;</p><p>What’s needed- Preferred Qualifications:&nbsp;</p><ul style=\"padding-left: 72px;\"><li>Master’s or PhD in Data Science, Statistics, Computer Science, or a related field</li><li>6+ years of experience in advanced analytics, machine learning, or AI</li><li>Experience deploying models into production environments (e.g., APIs, cloud platforms such as AWS, Azure, or GCP)</li><li>Proficiency with big data technologies (e.g., Spark, Hadoop)</li><li>Experience with MLOps practices, including model monitoring, versioning, and lifecycle management</li><li>Domain expertise in areas such as retail, e-commerce, pricing, supply chain, or customer analytics</li><li>Experience leading project workstreams or mentoring junior team members</li><li>Demonstrated ability to deliver solutions that resulted in measurable business outcomes (e.g., % revenue uplift, cost savings, efficiency gains)</li><li>Experience building and deploying Marketing Mix Models (MMM) or Multi-Touch Attribution (MTA) solutions&nbsp;</li><li>Experience working with customer lifetime value (CLV) modeling and lifecycle analytics&nbsp;</li><li>Experience developing personalization or recommendation systems in a marketing or e-commerce context&nbsp;</li><li>Familiarity with causal inference techniques and incrementality measurement frameworks&nbsp;</li><li>Experience supporting marketing organizations (e.g., paid media, CRM, loyalty, digital analytics)</li></ul><p>&nbsp;</p><p>We Offer:</p><ul style=\"list-style-type: disc;\"><li>Inclusive culture with associate-led Business Resource Groups</li><li>22 days of PTO and Holiday Schedule (7 observed paid holidays + 1 floating holiday)</li><li>Online and Retail Discounts, Company Match 401(k), Physical and Mental Health Wellness programs, and more!</li></ul><p>&nbsp;</p><p>The salary range represents the expected compensation for this role at the time of posting. The specific base pay may be influenced by a variety of factors to include the candidate's experience, skill set, education, geography, business considerations, and internal equity. In addition to base pay, this role may be eligible for bonuses, or other forms of variable compensation.</p><p>&nbsp;</p><p>&nbsp;</p>",
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