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

Qualcomm•San Diego, CA

1d•$108,000 - $162,000

About The Position

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.

Requirements

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.
Bachelor's degree and 4+ years of Engineering Operations or related work experience.
Associate's degree and 6+ years of Engineering Operations or related work experience.
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.

Nice To Haves

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.

Responsibilities

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.
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.
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.
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.