Manager, Data Analytics

Samsung•Plano, TX

10d

About The Position

The Data Analytics Manager provides Samsung.com day-to-day operators with insights to help shape business direction. The manager leads the Data Team in aligning tasks and initiatives with leadership’s business goals, analyzing large datasets, building models, and identifying operational trends and anomalies across lines of business. This is a highly visible role with broad organizational impact, partnering with product, engineering, business management, marketing, customer service, and other cross-functional teams to understand the business and improve customer experiences and operations. The position leads a team of three (two data engineers and one data analyst/scientist), develops the team to meet business demands, and manages incoming business requests for data-related work. It combines strategic and tactical planning for eCommerce operations with data analysis, reporting, dashboarding, training, vendor-partner support, and KPI monitoring. Work is generally performed in an office environment, with frequent additional hours beyond the normal schedule and periodic time-sensitive work stress. The role involves a high level of responsibility and access to confidential company data.

Requirements

At least 6 years of experience in a similar eCommerce or Operations role.
Degree in Data Science, Business Analytics, Economics, or a related field.
Ability to lead a team and motivate individuals to perform at their best.
Strong experience in data collection, cleaning, and analysis.
Proficiency with JIRA, Confluence, Excel, SQL, Python or another programming language, and data visualization tools such as Tableau or Power BI.
Experience with cloud platforms; Google Cloud Platform (GCP and Dataform) and AWS are mentioned.
Excellent communication skills and ability to explain complex data insights in simple terms.
Ability to collaborate effectively and work under pressure.
Familiarity with e-commerce platforms and industry metrics.
Experience using Tableau and Microsoft PC software, including extensive use of Excel spreadsheets, Word, and Access, as well as SAP or similar sales order management software.
Ability to perform the essential duties in an office environment, operate a computer keyboard and view a video display terminal for prolonged periods (50% of work time), and move or transport equipment most often weighing under 25 pounds.
Ability to work under periodic or cyclical time pressures and frequently work additional hours beyond the normal schedule.

Nice To Haves

Experience with high-volume direct-to-consumer eCommerce fulfillment or returns, demonstrating process and KPI improvements to scale growth; operations or logistics experience is a strong advantage.
Experience with Google Cloud Platform (GCP and Dataform) or AWS.

Responsibilities

Lead and develop a team of three data professionals: two data engineers and one data analyst/scientist.
Receive data-related requests from the business and align team resources to deliver effective solutions.
Drive strategic and tactical planning for eCommerce operations from a data perspective and present recommendations to leadership.
Collect, organize, and analyze large datasets from multiple sources to identify customer behavior and operational trends.
Prepare reports and dashboards that communicate findings and support decision-making.
Conduct onboarding and training for operational staff on analytical and AI frameworks used to access, interpret, and leverage data and reports.
Identify opportunities to improve operations and recommend data-driven solutions to increase revenue.
Collaborate with cross-functional teams to support data accuracy and relevance and communicate analytical results effectively.
Use statistical methods and visualization tools to identify patterns, correlations, and anomalies.
Keep current with analytical tools and techniques and support colleagues with data-analysis best practices.
Present findings and recommendations clearly to stakeholders to facilitate decisions.
Help manage eCommerce vendor partners, including providing input on contract reviews, SLA adherence, budgeting, cost analysis, and procurement.
Partner with customer service to understand consumer pain points and develop customer-experience improvement initiatives.
Collaborate with data warehouse and analytics teams on data ingestion from external third-party sources and adoption of a new dashboarding and visualization tool.
Monitor exception reports and KPIs for lead times, shipping time, backorders, and shipping exceptions; take action and support initiatives to improve direct eCommerce operational performance.