Description

Overview

Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

About Keysight AI Labs

Keysight accelerates innovation to connect and secure the world. Our solutions span wireless communications, semiconductors, aerospace & defense, automotive, and beyond. We combine measurement science, simulation, and advanced AI to help engineers design, simulate, and validate the world's most advanced systems.

About the AI Team

You'll join a cross-disciplinary R&D team pioneering data-driven innovation at Keysight.
We collaborate closely with domain experts in simulation, measurement, RF systems, and AI to transform scientific and engineering data into actionable insights.
Our environment bridges machine learning, data engineering, and experimental science, giving you access to unique high-fidelity datasets that drive next-generation design, modeling, and analytics capabilities.

About the Role

As a Senior Applied Data Scientist, you'll operate at the intersection of data engineering, data science, and machine learning. You'll design and implement large-scale data architectures, develop robust data pipelines, and build high-quality ML models that integrate simulation and measurement data from diverse domains.

Your work will directly influence Keysight's advanced R&D initiatives - from algorithm development to AI-assisted engineering tools.

Responsibilities

• Partner with internal engineering and data teams to identify key data sources, define feature requirements, and align data standards across organizations.
• Design, implement, and maintain data lakes, databases, and ETL/ELT pipelines (Snowflake, Databricks, SQL, Python).
• Integrate, clean, and align simulation, measurement, and operational data for scalable AI/ML model development.
• Conduct exploratory data analysis, dimensionality reduction (e.g., PCA), clustering, and regression to extract insights.
• Develop and validate ML models using tree-based methods (XGBoost, LightGBM, Random Forests) and Bayesian Optimization for tuning.
• Apply signal processing and data augmentation techniques to improve data quality and coverage.
• Document data lineage, feature definitions, and modeling rationale for reproducibility and transparency.
• Communicate insights and recommendations to stakeholders, influencing data-driven decisions across R&D and product teams.

Qualifications

Required Qualifications

• Master's or PhD in Data Science, Computer Science, Electrical Engineering, Statistics, or related field.
• 5+ years' experience as a Data Scientist / Applied Data Scientist, ideally in engineering or simulation-driven environments.
• Proven ability to build and maintain scalable data infrastructures (data lakes, schemas, pipelines).
• Strong programming skills in Python (pandas, numpy, scikit-learn), SQL, and optionally C++.
• Proficiency with Snowflake, Databricks, or similar big-data environments.
• Hands-on expertise in tree-based ML techniques and statistical modeling.
• Familiarity with Bayesian Optimization and feature engineering for time-series or signal data.
• Ability to move fluidly between data exploration, engineering, and modeling tasks.

Desired Qualifications

• Experience in data architecture design, schema governance, or cross-team data standards.
• Familiarity with Keysight simulation or measurement tools (e.g., ADS, RFPro, EMPro, Signal Studio, RaySim).
• Knowledge of MLOps principles for productionizing models and maintaining pipelines.
• Experience with metadata management and feature store design.
• Prior exposure to environments combining simulation and real-world measurement data.

Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***