Data Scientist Senior - Machine Learning

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

Our

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

Join

, a newly formed hub driving innovation in machine learning. As part of this growing team, you’ll have the chance to shape our AI strategy and make an immediate impact. Our work spans supervised and unsupervised learning, generative models, multimodal systems, reinforcement learning, and large language models.

Keysight accelerates innovation to connect and secure the world. From wireless communications and semiconductors to aerospace, defense, and automotive, we combine measurement science, simulation, and AI to help engineers design and validate the most advanced systems

About the AI Team

We are expanding the Team and 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.

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

• Keysight is an Equal Opportunity Employer.