Senior Data Scientist: Data Architecture & Features

Keysight Technologies; Barcelona; Presencial; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

A global technology company in Barcelona is seeking a Senior Applied Data Scientist. You will explore complex engineering data and architect scalable data infrastructures to support AI model development. Required qualifications include a Master’s degree in a quantitative field and at least 5 years in a relevant role. Strong skills in Python, SQL, and big data tools like Spark are essential. The role offers a dynamic environment with the opportunity to innovate and tackle complex data challenges.

Formación

• Master’s in Data Science, Statistics, CS, EE, or related quantitative field.
• 5+ years of experience in applied data science or hybrid DS/DE role.
• Expert proficiency in Python, SQL, and data manipulation libraries.
• Strong background in statistics, algorithms, and data structures.
• Experience with relational and NoSQL databases.

Responsabilidades

• Partner with internal experts to identify critical data sources.
• Architect and build scalable data lakes/databases.
• Clean, align, normalize, and integrate data from various sources.
• Develop and maintain ETL/ELT pipelines using SQL and Python.
• Perform EDA, feature engineering, and generate high-value insights.

Conocimientos

Python

SQL

Data manipulation libraries

Statistics

Data structures

Big data tools (Spark, Kafka)

Cloud platforms (Azure / AWS / GCP)

Educación

Master’s in Data Science, Statistics, CS, EE, or related quantitative field

Herramientas

Snowflake

Databricks

Hadoop

Docker

Kubernetes

Descripción del empleo

A global technology company in Barcelona is seeking a Senior Applied Data Scientist. You will explore complex engineering data and architect scalable data infrastructures to support AI model development. Required qualifications include a Master’s degree in a quantitative field and at least 5 years in a relevant role. Strong skills in Python, SQL, and big data tools like Spark are essential. The role offers a dynamic environment with the opportunity to innovate and tackle complex data challenges.