Data Scientist – CPSE Eng Ops (Opex Analytics & Automation)

Location: San Diego, California, United States of America

Department: Engineering Operations

Work Location: onsite

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Services Group, Engineering Services Group > Engineering Operations

General Summary:

We are seeking a highly skilled Data Scientist to support CPSE Eng Ops through advanced analytics, data science, and intelligent automation, with a strong focus on Operating Expense (Opex) planning, HC Management, forecasting, and reporting.

This role combines deep analytical judgment, hands-on Python delivery, and AI-enabled automation to transform CPSE Eng Ops workflows and decision support. The individual will work with complex enterprise operating expense and planning data, develop scalable analytics and AI solutions, and deliver management-ready insights to CPSE Eng Ops leadership. The role operates with limited supervision and plays a key role in continuously improving CPSE Eng Ops analytics, automation, and self-service capabilities.

Minimum Qualifications:

• Bachelor's degree and 4+ years of Engineering Operations or related work experience.
OR
Associate's degree and 6+ years of Engineering Operations or related work experience.
OR
High School Diploma or equivalent and 8+ years of Engineering Operations or related work experience.

*Completed advanced degrees in a relevant field may be substituted for up to two years (Master’s = one year, Doctorate = two years) of work experience.

Data Science, AI & Automation

• Build and maintain Python-based datasets, analytical models, and automation workflows using enterprise operating expense and planning data.
• Design and deploy scalable analytics and automation solutions to reduce manual reporting and recurring analysis effort.
• Apply statistical, forecasting, and AI-enabled techniques where appropriate, ensuring explainable, auditable, and governance-compliant outputs.
• Develop AI/ML and GenAI solutions (including LLMs, AI agents, and context-aware orchestration such as Model Context Protocol where applicable) for CPSE Eng Ops use cases such as forecasting, anomaly detection, reconciliations, and operational reporting support.
• Integrate analytical and AI solutions with enterprise systems such as Oracle ERP, SAP, TM1 systems.
• Validate data quality, logic, and outputs to meet CPSE Eng Ops governance, controls, and audit requirements.

Collaboration, Adoption & Enablement

• Enable adoption of analytics and automation through standardized dashboards, templates, and self‑service tools.
• Create high‑quality documentation covering logic, assumptions, reconciliations, and usage guidance.
• Drive change management by developing training materials and partnering with stakeholders to scale usage.
• Collaborate with IT and enterprise teams to align solutions with data, security, and AI governance standards.

Opex Analytics, HC & CPSE Eng Ops Insights

• Analyze Opex actuals, budget, and forecast data to identify key drivers, risks, and variance trends.
• Develop repeatable analytics for run-rate analysis, spend trends, target utilization, and forecast accuracy.
• Translate CPSE Eng Ops business questions into structured analytical approaches, metrics, and assumptions.
• Deliver clear, management-ready insights and visualizations to CPSE Eng Ops leadership.

Strategic Contribution

• Define KPIs and success metrics to measure the impact of analytics and AI initiatives in CPSE Eng Ops.
• Stay current with advancements in generative AI, agent‑based systems, and enterprise AI governance.

• Present insights, proposals, and recommendations to senior CPSE Eng Ops leaders and executive stakeholders.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Finance, Accounting, Economics, Engineering, or related field.
• 4+ years of relevant experience in data science, analytics, or finance analytics roles.
• Strong analytical and problem-solving skills with structured enterprise datasets.
• Proficiency in Python for data analysis, modeling, and automation.
• Ability to communicate analytical insights effectively to non-technical stakeholders.

Preferred Qualifications

• Master’s degree in a quantitative or finance, operations related discipline.
• Experience supporting Opex, HC Management or cost management functions.
• Exposure to AI/ML or LLM-based solutions in enterprise environments.
• Experience with automation tools such as Power Automate or n8n.
• Experience with Data bricks, Power BI or Tableau.

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EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

 

Pay range and Other Compensation & Benefits:

$108,000.00 - $162,000.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.

If you would like more information about this role, please contact Qualcomm Careers.