Strategic Data Analytics Lead (Hybrid)

General Motors; Sunnyvale (CA); Hybrid; USD 129,000 - 198,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Tuition assistance programs

GM vehicle discounts

Retirement savings plan

Job summary

General Motors is seeking an experienced data analyst to lead analytics across the Scaled Engineering Operations organization and support management of high priority technical services. You will develop metrics, guide initiatives, and partner with Engineering to support complex services used to deliver results.

You will drive KPI development, quantify efficiency and data quality, and communicate impact to leadership while coordinating with Labeling, Analysis, and Protocol teams.

Qualifications

• 5+ years of work experience in analytics, consulting, finance, or operations.
• Proficient in SQL or Python for metrics and KPIs.
• Experience building data-driven strategies in complex nascent industries.
• Ability to present executive-level analyses and recommendations.
• Proven track record of influencing stakeholders and building consensus.
• Experience in vendor and external partner management.

Responsibilities

• Identify and launch new processes and tools that measure efficiency and data quality.
• Lead projects to improve efficiency and/or quality.
• Scope and implement analyses, experiments, pilots informing product direction.
• Understand datasets and design improvements with stakeholders.
• Track and communicate progress to leadership showing impact.
• Support ad-hoc analytics requests.

Skills

SQL

Python

KPI development

Executive communication

Stakeholder management

Vendor management

Analytical thinking

Job description

General Motors is seeking an experienced data analyst to lead analytics across the Scaled Engineering Operations organization and support management of high priority technical services. You will develop metrics, guide initiatives, and partner with Engineering to support complex services used to deliver results.

You will drive KPI development, quantify efficiency and data quality, and communicate impact to leadership while coordinating with Labeling, Analysis, and Protocol teams.