Descripción

The Role

The Safety Field Investigations (SFI) Data Analyst supports Global Field Action Execution by leading data analysis, reporting, and data pipeline activities that improve field action decision-making and operational execution. This role builds on the current SFI Analyst scope by combining VIN population analysis, cost modeling, internal reporting, and database support with modern data engineering and visualization capabilities.

The ideal candidate brings strong analytical and problem-solving ability, works effectively across global teams, and can translate complex operational and engineering data into actionable business insights.

What You’ll Do (Responsibilities):

Lead field action VIN population analysis and definition to determine vehicle eligibility, support customer contact strategy, and help complete required documentation.

Design, maintain, and improve data pipelines and data workflows that support field action analytics, reporting, and operational decision-making.
Perform data preprocessing, cleansing, validation, and feature engineering to improve data quality and usability for analysis.
Develop cost estimates and analytical models to support corporate financial accruals and business planning.
Create and distribute internal field performance and field action communications for global and regional stakeholders.
Support the administration, enhancement, and data governance of the Global SFI database and related analytical tools.
Build dashboards, scorecards, and self-service reporting solutions using Tableau and Power BI to monitor field action performance and trends.
Use SQL, Databricks, Hadoop, Pandas, and NumPy to analyze large datasets, automate recurring analysis, and generate actionable insights.
Partner with engineering, operations, and global teams to solve complex problems, align on data definitions, and drive consensus on key decisions.
Apply knowledge of automotive engineering terms, systems, and components to interpret data and support field action execution.

Your Skills & Abilities (Required Qualifications):

Bachelor’s degree in Data Analytics, Computer Science, Information Systems, or a related field; equivalent relevant experience may be considered.
5+ years of related experience or demonstrated proficiency in analytical and technical roles.
Strong oral and written communication skills.
Strong interpersonal skills and the ability to work effectively with cross-functional and global partners.
Demonstrated ability to work independently, solve highly complex problems, and lead teams to consensus when needed.
High level of analytical ability, especially when working with unusual or difficult problems.
Strong experience with SQL and data analysis in large, complex datasets.
Hands-on experience with data engineering and big data environments such as Databricks and Hadoop.
Experience building and maintaining data pipelines and performing data preprocessing and feature engineering.
Experience creating dashboards and visual analytics using Tableau and Power BI.
Proficiency with Python-based analytics tools such as Pandas and NumPy.
Strong estimating, planning, and organizational skills.

What Can Give You a Competitive Edge (Preferred Qualifications):

Experience with automotive components and systems.
Experience with GM systems such as QDAP and other performance integration-related applications.
Experience with GM Data Structure
Advanced proficiency in Excel, Access, or other analytical tools.
Good project management skills.
Experience developing enterprise data models, automated reporting, or scalable analytics solutions in operational environments.

#LI-KE2

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

Este puesto se clasifica como híbrido. Esto significa que se espera que el candidato seleccionado se presente en una ubicación específica al menos 3 veces por semana {o con otra frecuencia indicada por su líder}.

Este puesto podría ser elegible para beneficios de relocalización.

Información sobre diversidad

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Declaración de igualdad de oportunidades en el empleo (EE.UU.)

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Adecuaciones (EE.UU. y Canadá)

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