Manager, DTC Advanced E-Commerce Analytics & Go-to-Market Intelligence (Smartphones)
Position Summary Headquartered in Englewood Cliffs, N.J., Samsung Electronics America, Inc. (SEA) is a leader in mobile technologies, consumer electronics, home appliances and enterprise solutions. From our humble beginnings to our position today as a tech leader, our passion for innovation has been the common thread throughout our history. We’ve grown into one of THE most recognized global brands. We consider ourselves “relentless pioneers” that push boundaries and defy barriers. The company pushes beyond the limits of today’s technology to provide groundbreaking connected experiences across its large portfolio of products and services, including mobile devices, home appliances, home entertainment, 5G networks, and digital displays. As EPA’s ENERGY STAR® Corporate Commitment Partner, SEA is dedicated to making a positive impact on the environment through its eco-conscious products, practices, and operations. People | Excellence | Change | Integrity | Co-Prosperity Role and Responsibilities Position Summary The Manager of DTC Advanced E-Commerce Analytics & Go-to-Market Intelligence is a technical leadership role responsible for designing, implementing, and optimizing data-driven systems that power Samsung.com’s direct-to-consumer growth. This role applies statistical modeling, data engineering, automation, and quantitative analysis to forecast demand, optimize conversion funnels, and support large-scale product launches. Operating with a Product Owner mindset, this position owns the analytical architecture for flagship smartphone launches, including Fold/Flip and other Galaxy Flagship, by leveraging advanced SQL, automated Excel-based modeling, enterprise BI platforms, and predictive analytics. The role serves as a technical bridge between engineering, data, and business teams, translating complex and ambiguous problems into scalable, repeatable data solutions. Core Technical & Analytical Responsibilities 1. Category Performance Analytics and P&L Decision Support Own quantitative and statistical analytical frameworks supporting end-to-end category performance, including revenue, units, ASP, margin, conversion, traffic, attachment rate, and inventory health. Perform SKU-level and category-level quantitative analysis to identify performance drivers, risks, and optimization opportunities. Support category P&L management through quantitative modeling and scenario simulations across pricing, promotions, assortment mix, and inventory positioning. Develop executive-ready performance readouts with clear insights, implications, and data-backed recommendations. 2. Business Intelligence & Analytics Platform Architecture Architect and govern enterprise-level Tableau dashboards that deliver real-time and historical visibility into DTC performance metrics. Implement advanced Tableau features including calculated fields, parameters, LOD expressions, filters, and blended data sources. Design executive scorecards that function as a governed analytical layer supporting strategic decision-making 3. Inventory, Supply Chain & Demand Signal Analytics Monitor inventory coverage, sell-through, weeks of supply, aging, and out-of-stock risk using quantitative thresholds and predictive signals. Identify early demand shifts and inventory risks, partnering with Supply Chain and Operations on corrective actions. Support assortment and inventory decisions to balance growth, margin protection, and operational efficiency. 4. Advanced Quantitative Modeling, Forecasting & Excel Automation Build and maintain quantitative models in Excel using advanced formulas, Power Query, scenario analysis, and sensitivity modeling to support: Revenue and demand forecasting Inventory optimization and risk modeling Promotional lift, elasticity, and ROI analysis Pricing, margin, and P&L simulations Develop VBA/Macro-based automation to streamline recurring analytical workflows and improve reproducibility. Enable stakeholders to perform structured what-if analyses via scalable, parameter-driven modeling frameworks. 5. Technical & Cross-Functional Leadership Partner with Product, Engineering, Marketing, Pricing, Supply Chain, CRM, Legal, and Finance teams to align analytical solutions with system and business requirements. Serve as a technical subject-matter expert for analytics methodologies, modeling techniques, and data governance standards. Lead cross-functional stakeholders through structured analytical narratives grounded in quantitative evidence. 6. Go-to-Market Operation & Product Launch Analytics Lead data-driven and model-based analytical support for end-to-end smartphone product launches, including pre-launch forecasting, launch readiness metrics, and post-launch performance evaluation. Partner with UX, Product, and Engineering teams to evaluate digital UI/UX enhancements using funnel analytics, behavioral data, and experimentation results to improve conversion efficiency. Apply structured analytical frameworks to evaluate conversion funnels, pricing strategies, promotional effectiveness, and merchandising performance. Conduct post-launch statistical analyses to extract learnings and improve future go-to-market execution. 7. KPI Frameworks, Predictive Analytics & Decision Science Define and operationalize standardized KPI frameworks across traffic, conversion, revenue, margin, inventory health, and customer behavior. Design and analyze A/B and multivariate experiments to quantify the impact of pricing, promotions, merchandising, and UX changes on conversion rate, engagement, and revenue. Develop automated weekly, monthly, and quarterly reporting systems to support technical business reviews. Translate analytical outputs into quantitative, data-backed recommendations for senior leadership. Forecast Modeling: Perform historical back-testing and scenario simulation to improve forecast accuracy for new product categories. Funnel Decomposition: Quantitatively deconstruct customer journeys to identify system-level inefficiencies and optimize marketing ROI. Pricing & Elasticity Modeling: Model price-response relationships to evaluate volume lift, margin impact, and profitability trade-offs. 8. Data Engineering, SQL Analytics & Workflow Automation Architect and maintain automated Single Version of Truth (SVOT) data pipelines and GAAP-aligned P&L frameworks using advanced SQL, Power Query, and VBA/Macros to consolidate Finance, Supply Chain, CRM, and e-commerce data. Design, write, and optimize complex SQL queries (multi-table joins, CTEs, aggregations, performance tuning) to process and analyze large, structured datasets at scale. Eliminate manual reporting dependencies through workflow automation, improving system reliability, accuracy, and operational efficiency. Perform SKU-level, cohort-based, and funnel-level analyses to identify statistically significant drivers of conversion, revenue, and margin performance. Develop enterprise-grade Tableau dashboards for real-time monitoring, trend detection, and anomaly analysis. Analyze clickstream and funnel data from Adobe Analytics (or equivalent platforms) to identify friction points and conversion optimization opportunities. Skills and Qualifications Required Qualifications Education Bachelors or Masters in Engineering, Data Analytics, Statistics, Industrial Engineering, Applied Mathematics, or Economics. Technical Skills & Experience Advanced SQL: complex joins, query optimization, data validation Advanced Excel: VBA/Macros, Power Query, quantitative modeling, scenario analysis Business Intelligence: Tableau (dashboard architecture, calculated fields, LOD expressions) or Power BI 6+ years of experience in large-scale DTC, e-commerce, or data-intensive environments Demonstrated ability to manage and optimize $1B+ portfolios using quantitative, data-driven frameworks Preferred Qualifications Experience supporting enterprise DTC or e-commerce analytics platforms Exposure to pricing analytics, category management, or demand planning systems Strong experience working with large, multi-source datasets and ambiguous technical problem statements Excellent technical communication and data storytelling skills for executive audiences #LI-RL3 Life @ Samsung - Benefits @ Samsung - Regular full-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more. 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