Lead Analyst, Data - Bloomington, CA

GXO•Bloomington, CA

2d•Hybrid

About The Position

GXO Warehouse Company, Inc. is seeking a Lead Analyst, Data for their Bloomington, California location. This role involves collecting, cleaning, and organizing data from various sources, analyzing trends, and developing reports and visualizations to provide insights to leadership. The analyst will also develop statistical models, create applications for data querying and visualization, and apply statistical techniques to identify patterns. Collaboration with cross-functional teams, including operations and industrial engineers, is crucial for implementing Lean methodologies and driving continuous improvement. The position requires a Bachelor's Degree in Data Analytics or a related field, with at least two years of progressive experience in SQL, VBA, Power BI or Qlik Sense, Python, Advanced Excel, Microsoft Access, Data Mining, Data Analysis, Data Visualization, ERP/SAP systems, Lean/Six Sigma methodology, and Logistics and Warehousing. The role is eligible for telecommuting from home within a reasonable commuting distance from Bloomington, CA, but will require physical presence at the worksite several days a week. Travel is required approximately 10% of the time to support sites in Arizona, Georgia, and North Carolina.

Requirements

Bachelor’s Degree in Data Analytics or closely related field.
Data modeling knowledge.
Two (2) years of post-bachelor’s progressive experience in all of the following: SQL (Structured Query Language)
VBA (Visual Basic for Application) programming
Power BI or Qlik Sense
Python Language
Advanced Microsoft Excel
Microsoft Access
Data Mining, Data Analysis, Data Visualization
ERP/SAP system
Lean / Six Sigma methodology
Logistics and Warehousing

Responsibilities

Collect, clean, and organize data.
Analyze results and develop recurrent and ad hoc reporting.
Acquire data from varied internal and external sources.
Identify, analyze and interpret trends or patterns in complex data sets.
Troubleshoot, optimize and audit existing reporting to maintain reporting integrity.
Provide data visualizations and reporting to convey complex analysis in a digestible fashion.
Understand operational challenges and derive/collect data needed to provide insight to leadership.
Provide actionable reporting to drive operational functions.
Maintain tools and environments used by the analytics team.
Develop statistical models to forecast demand, optimize inventory, and improve operational efficiency.
Develop applications to query databases, collect information, visualize data, and provide search functionality for operations teams.
Apply regression analysis, time series analysis, and other statistical techniques to identify patterns, trends, and anomalies in data.
Engage with cross-functional teams, including operations, finance, engineering, and maintenance, to understand their data needs and develop analytical solutions to address business challenges.
Work closely with industrial engineers to implement Lean methodologies and drive continuous improvement efforts.
Implement Lean initiatives to reduce lead times, eliminate bottlenecks, and improve overall operational flow.
Identify opportunities for automation and process standardization to improve efficiency and reduce errors.