Applied Data Scientist: ML & Data Lakes for R&D AI

Keysight Technologies SAles Spain SL.; Santa Rosa (CA); On-site; USD 118,000 - 196,000; Full time

Benefits offered by this job

Medical/Dental/Vision

401(k) Plan

Flexible Time Off

Paid Holidays

Health Savings Account

Job summary

Keysight Technologies is seeking an Applied Data Scientist in California to design and implement large-scale data architectures, build ML models, and integrate simulation and measurement data across domains.

You will collaborate with data and engineering teams to create data lakes, ETL/ELT pipelines, and feature-rich datasets, using Python, SQL, Snowflake, and Databricks to drive AI-enabled R&D and product insights.

Qualifications

• Master’s or PhD in Data Science, Computer Science, Electrical Engineering, Statistics, or related field.
• 1+ years’ experience as a Data Scientist / Applied Data Scientist.
• 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.

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.

Skills

Python

SQL

Data science

Machine learning

Time-series

Feature engineering

Data pipelines

Big data

Education

Master's or PhD in Data Science

Tools

Snowflake

Databricks

SQL databases

Python tooling

Job description

Keysight Technologies is seeking an Applied Data Scientist in California to design and implement large-scale data architectures, build ML models, and integrate simulation and measurement data across domains.

You will collaborate with data and engineering teams to create data lakes, ETL/ELT pipelines, and feature-rich datasets, using Python, SQL, Snowflake, and Databricks to drive AI-enabled R&D and product insights.