Ranking: 24
As a Data Scientist, you will play a key role in transforming raw data into actionable insights. You'll work closely with cross-functional teams to design and deploy data pipelines, build predictive models, and drive decision-making with data at scale.
Design, develop, and maintain data pipelines using Python and PySpark .
Perform data quality Investigation analysis and data remediation activities on AFC area (Based on Machine learning models).
Leverage strong SQL skills to extract, manipulate, and analyze data from complex relational databases.
Apply machine learning models to solve real business problems, from prototype to production.
Collaborate with engineers, analysts, and business stakeholders to turn data into valuable insights.
Ensure data quality, consistency, and performance across datasets and models.
5+ years of professional experience in Data Science or related fields.
Proficiency in Python and PySpark for large-scale data processing.
Advanced knowledge of SQL for querying and transforming complex datasets.
Strong foundational understanding of machine learning models (classification, regression, etc.).
English proficiency at B2 level or higher (both written and verbal).
Banking Experience
Experience deploying ML models into production.
Familiarity with cloud platforms (AWS, GCP, or Azure).
Exposure to data visualization tools (eg, Power BI, Tableau).
As a Data Scientist, you will play a key role in transforming raw data into actionable insights. You'll work closely with cross-functional teams to design and deploy data pipelines, build predictive models, and drive decision-making with data at scale.
Design, develop, and maintain data pipelines using Python and PySpark .
Perform data quality Investigation analysis and data remediation activities on AFC area (Based on Machine learning models).
Leverage strong SQL skills to extract, manipulate, and analyze data from complex relational databases.
Apply machine learning models to solve real business problems, from prototype to production.
Collaborate with engineers, analysts, and business stakeholders to turn data into valuable insights.
Ensure data quality, consistency, and performance across datasets and models.
5+ years of professional experience in Data Science or related fields.
Proficiency in Python and PySpark for large-scale data processing.
Advanced knowledge of SQL for querying and transforming complex datasets.
Strong foundational understanding of machine learning models (classification, regression, etc.).
English proficiency at B2 level or higher (both written and verbal).
Banking Experience
Experience deploying ML models into production.
Familiarity with cloud platforms (AWS, GCP, or Azure).
Exposure to data visualization tools (eg, Power BI, Tableau).
About the projects you will work on
You will work 100% remotely from wherever you decide. Sometimes you may have face-to-face meetings and for that reason you have to reside in Spain or in the European Union.
You will work on projects with a leading company in digital transformation with a passion for technology and innovation in sectors such as banking (35 of the main banks worldwide work with our client), insurance, industrial and automotive in Big Data projects, Blockchain, AI, Cloud, among others.
About the client
About the process and your contractual relationship
If you are interested in this offer, we will enroll you in the process and submit your application, blindly, that is, without your contact details, to the technical and human resources department so that they can evaluate your profile and your financial expectations.
If the answer is positive, we organize the meetings so that the client knows you and explains the project in detail.
If after the meeting both parties agree on the conditions, you receive a firm offer to work with us or directly be hired by the client.
