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# Applied Data Scientist

- **Company:** Keysight Technologies
- **Location:** Barcelona, Spain
- **Salary:** €117,750.0 - €196,250.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, C++ (Programming Language), Computer Programming, Databases, Data Architecture, Data Governance, Extract Transform Load (ETL), Document-Oriented Databases, Python (Programming Language), Machine Learning, Meta-Data Management, NumPy, Operational Data Store, Signal Processing, SQL Databases, Feature Engineering, Snowflake, Pandas, Data Lakes, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** July 14, 2026
- **Apply:** https://www.jobleads.com/es/job/e9341f9ecce4dab4a2d3bb7f601958faf

## About the Role

* 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., * Experience in data architecture design, schema governance, or cross-team data standards.
 * 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.

## Description

* 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.


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