Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. The company's innovative technology enables new possibilities across enterprise, cloud and AI, and carrier architectures. Marvell offers field-proven solutions for high-speed optical interconnects and transceivers, used in a wide array of enterprise, carrier, small medium business, industrial, and cloud data center applications. The company is actively driving innovation in response to megatrends like cloud services, video streaming, 5G wireless, and AI/ML, which demand higher bandwidth, lower power, and smaller footprints.

About the Position

Introduction

Marvell is looking for a highly motivated Staff Data Science Engineer to join their team focusing on hardware and silicon validation. This role involves leveraging data science, statistical modeling, and machine learning techniques to optimize and accelerate the validation cycles for high-speed DSP (Digital Signal Processing) systems.

Responsibilities

Build Data Pipelines: Design and develop scalable data pipelines for ingesting, processing, and storing large volumes of DSP validation and test data.
Data Analysis & Modeling: Apply statistical analysis and machine learning techniques to identify patterns, detect anomalies, and support root-cause analysis.
Visualization & Dashboarding: Create intuitive dashboards and visualizations to help AE/FAE and validation engineers interpret test results and debug issues quickly.
Cloud-Based Analytics: Utilize cloud technologies for efficient processing and analysis of large-scale datasets, enabling near real-time insights.
Collaboration with Engineering Teams: Work closely with hardware, firmware, and validation engineers to understand data, define metrics, and translate complex data into actionable insights.
Automation & Efficiency: Develop tools and workflows to reduce manual debugging efforts and accelerate validation cycles.

Requirements

Minimum Qualifications

Bachelor’s degree in Computer Science, Electrical Engineering, or a related field with 3–5 years of industry experience, or Master’s/PhD with 1-2 years of experience.
Strong foundation in data analysis, statistical modeling, and machine learning.
Proficiency in Python (pandas, numpy, matplotlib/seaborn, scikit-learn, or similar).
Experience with data visualization tools like Tableau or equivalent (e.g., Power BI, Superset).
Experience working with large datasets, including data cleaning, transformation, and feature engineering.

Preferred Qualifications

Experience with cloud platforms (e.g., Amazon Web Services, Snowflake, Databricks).
Familiarity with data pipeline development (ETL, streaming, batch processing).
Experience with time-series data analysis or signal/data from hardware systems.
Exposure to DSP systems, networking, or semiconductor validation workflows.
Experience with SQL and database systems (e.g., Snowflake, PostgreSQL).
Knowledge of machine learning for anomaly detection, prediction, or optimization.
Familiarity with dashboard design for engineering workflows.

Benefits

Marvell is committed to providing exceptional, comprehensive benefits that support employees at every stage. Offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights include an employee stock purchase plan with a 2-year look back, family support programs, robust mental health resources, and recognition/service awards.

About Company

How to Apply

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status. Applicants requiring reasonable accommodation during the selection process should contact Marvell HR Helpdesk at TAOps@marvell.com. Candidates are not permitted to use AI tools during interviews without prior instruction from the interviewer; misuse will result in disqualification.