Role Description We are looking for a Senior Data Scientist to develop and deploy advanced analytics and AI solutions that drive business impact in the Consumer Insights and Analytics team. As a Strategic Partner to Marketing and Sales teams, success in this role requires a strong analytical mindset, expertise in building machine learning models, optimizing performance, and integrating cutting-edge technologies to enhance decision-making and automation. Key Responsibilities - Advanced Analytics & Insights: Develop and implement data science solutions, leveraging advanced analytics to drive data-driven decision-making, optimize business performance, and support Consumer Insights & Analytics priorities. - Data Analysis & Modeling: Analyze large and complex datasets to identify patterns, build statistical and machine learning models, and solve critical business problems using big data technologies like Databricks, Azure ML, and Apache Spark, as well as strong data visualization for structured storytelling to drive impactful business decisions. - Developing Advanced Models: Design deep learning and natural language processing models to analyze complex data across business processes. - Model Monitoring & Performance Optimization: Continuously track, evaluate, and refine deployed models to maintain accuracy and relevance over time. - AI Research & Evaluation: Research, test, and evaluate AI technologies to ensure the best tools and platforms are used for achieving business objectives. - Enhancing Analytical Capabilities: Integrate the latest data science innovations into product solutions, enhancing data, analytical, and automation capabilities. - Cross-Functional Collaboration: Work closely with cross-functional teams and stakeholders to provide expertise across omnichannel analytical projects and ensure alignment with business goals. - Tool Development & Maintenance: Build, maintain, and improve analytics tools to enhance capabilities and accelerate speed to value. Qualifications - Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Mathematics, Physics, Operations Research, Statistics, or a related field. - 5+ years of experience as a Data Scientist, Machine Learning Engineer, or Applied Scientist, specializing in computer vision, natural language processing, or data synthesis. - Experience developing and deploying advanced analytical models and algorithms. - Experience applying machine learning techniques, including Regression, Clustering, Probability Networks, Artificial Intelligence (AI), and Deep Learning. - Hands-on programming experience in Python and R, leveraging advanced cognitive and machine learning methods to solve business challenges. - Experience working with relational database and cloud computing technologies such as Databricks, Snowflake, AWS, Azure ML and AMC, Big Query. - Experience in transforming raw data into meaningful features for machine learning models. - Expertise in handling missing data, scaling, encoding categorical variables, and dimensionality reduction techniques. - Hands-on experience in designing and analyzing A/B tests and other experimental methodologies. - Hands-on experience in causal inference techniques to measure the impact of business decisions. Skills - Experience visualizing and presenting data-driven insights using Power BI and Tableau. - Experience in developing recommendation engines for applications such as sales, customer targeting, or supply chain optimization. - Experience in building and implementing optimization models to enhance decision-making processes. - Familiarity with agile methodologies and rapid prototyping in data science projects. - Strong knowledge of industry-standard tools and methodologies for model training, statistical analysis, and machine learning deployment. - Experience working with CPG and ecommerce data sets, including retail analytics and advertising data, is a plus. - Candidates that have experience working with AMC (Amazon Marketing Cloud) and Amazon advertising and sales data will be given priority consideration. Compensation and Benefits - The approximate pay range for this position is $130,000 to $160,000. - Nestlé offers performance-based incentives and a competitive total rewards package, which includes a 401k with company match, healthcare coverage, and a broad range of other benefits. Inclusivity Statement It is our business imperative to remain a very inclusive workplace. To our veterans and separated service members, you're at the forefront of our minds as we recruit top talent to join Nestlé. The skills you've gained while serving our country, such as flexibility, agility, and leadership, are much like the skills that will make you successful in this role.

• Define how marketing and customer data is captured, structured, modeled, and reported across the organization • Own the end-to-end marketing measurement strategy across paid media, SEO, lifecycle marketing, affiliate, social, website, and revenue analytics • Define and maintain attribution models including first-touch, last-touch, multi-touch, and blended attribution • Establish source-of-truth logic for key business metrics including: Customer Acquisition Cost (CAC), Return on Ad Spend (ROAS), Customer Lifetime Value (LTV), Funnel conversion rates, Retention metrics, Payback period, Channel performance and contribution • Identify gaps in tracking, reporting, attribution, and data quality • Partner with leadership to prioritize analytics initiatives based on business impact • Define analytics requirements across the marketing data lifecycle • Collaborate with data engineers and developers on: • Event tracking architecture • Attribution persistence • Identity resolution and customer stitching • Data ingestion pipelines • Reporting-ready data models • Revenue reconciliation • Validate datasets and reporting logic within BigQuery or similar cloud data warehouse environments • Ensure marketing and product data can be accurately joined across systems • Own event taxonomy and tracking requirements across web, lifecycle, checkout, and product experiences • Partner with developers to ensure accurate implementation of: • Google Analytics 4 (GA4) • Google Tag Manager (GTM) • Meta Pixel and Conversions API (CAPI) • Google Ads tracking • Hyros and attribution platforms • Intercom and customer engagement tools • Maintain UTM governance and campaign naming conventions • Ensure click IDs and attribution parameters are captured and persisted correctly • Build or oversee dashboards and reporting systems using: • Tableau • Looker Studio • Power BI • Similar BI and analytics platforms • Create reporting frameworks and executive KPI dashboards • Translate complex analytics findings into clear business insights and recommendations • Support weekly and monthly business reviews with actionable reporting narratives • Create QA processes for analytics implementation and reporting accuracy • Monitor tracking integrity and proactively identify anomalies or reporting discrepancies • Maintain analytics documentation and reporting standards • Ensure stakeholders understand limitations or directional nature of data when applicable

Role Description The Lead Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies, and improved customer experience. This role assists in the development of the Home Depot advanced analytics infrastructure that informs decision making by applying expertise of both business and Advanced Analytics Modeling techniques. Lead Data Scientists focus on seeking out business opportunities to leverage data science as a competitive advantage. As a Lead Data Scientist, you will be responsible for large data science projects, identifying opportunities to leverage best technology and approach, and mentoring data scientists on the project team. This role is expected to own the library of reusable algorithms for future use, ensuring developed codes are documented. This role supports the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process. In addition, this role leads data science communities across several business units. Key Responsibilities - 30% Solution Development - Utilize expertise when designing and developing algorithms and models to use against large datasets to create business insights. - Make appropriate selection, utilization, and interpretation of advanced analytics methodologies. - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners. - Clearly communicate impacts of recommendations to drive alignment and appropriate implementation. - 25% Project Management & Team Support - Lead and manage large and complex projects and teams. - Provide direction on prioritization of work and ensure quality of work. - Provide mentoring and coaching to more junior roles to support their technical competencies. - Collaborate with managers and team in the distribution of workload and resources. - Support recruiting and hiring efforts for the team. - Serve as a technical subject matter expert (SME) for one or more data science methods, both predictive and prescriptive. - Lead data science communities across several business units. - 20% Business Collaboration - Leverage extensive business knowledge into solution approach. - Effectively develop trust and collaboration with internal customers and cross-functional teams. - Provide technical education on advanced analytics to data science community. - Partner with IT to understand potential for new tools and ways to maintain technical agility for data science. - Actively seek out new business opportunities to leverage data science as a competitive advantage. - 25% Technical Exploration & Development - Seek further knowledge on key developments within data science by attending conferences and publishing papers. - Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects. - Define best practices and develop clear vision for data analysis and model productionalization. - Ownership of library of reusable algorithms for future use, ensure developed code/models are documented. - Develop mastery in one or more prescriptive modeling techniques, like optimization, computer vision, recommendation, search or NLP. Qualifications - Must be eighteen years of age or older. - Must be legally permitted to work in the United States. - Demonstrated expertise in predictive modeling, data mining, and data analysis. - Demonstrated expertise utilizing statistical techniques to identify key insights that help solve business problems. Requirements - PhD in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience. - 10+ years of experience in business intelligence and analytics. - Expertise in a modern scripting language (preferably Python). - Expertise running queries against data (preferably with Google BigQuery or SQL). - Advanced knowledge of Microsoft Office Suite. - Expertise with data visualization software (preferably Tableau). - Expertise in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP. Company Description

• Drive healthcare innovation by enhancing automated clinical decision-making • Provide executive leadership for Data Science strategy and product implementation • Own the Evicore Medical Benefit Services (MBM) data science function • Manage predictive modeling, AI/ML, and workflow automation • Collaborate with clinical, operational, product, and technology leadership • Define and execute the organization’s AI strategy • Lead advanced analytics lifecycle from research to monitoring and governance • Build and mentor a high-performing data science organization • Ensure compliance with regulatory standards in AI and data science initiatives