Senior Data Scientist
J
JobgetherAutomotive Data
SpainFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- At least 8 years with Bachelor’s degree or 6 years with graduate degree, including substantial hands-on data science experience.
- Required Skills
- PythonSQLMachine LearningSnowflakeTableauSparkMLOps
Requirements
- At least 8 years of overall professional experience with a Bachelor’s degree, or at least 6 years of experience with a graduate degree.
- At least 4 years of experience working with large datasets and applying statistical or analytical methods to complex data problems.
- 4+ years of experience with statistical programming and data science tools (Python or Spark preferred; R or SAS considered a plus).
- At least 4 years of experience working with database technologies such as MS SQL, Snowflake, or MySQL.
- Strong knowledge of machine learning, statistical modeling, advanced feature engineering, model evaluation, and predictive analytics.
- Practical experience taking machine learning models into production, ideally including cloud-based MLOps environments and API-based model deployment.
- Comfortable working with cloud infrastructure and modern machine learning frameworks.
- Ability to communicate technical concepts clearly to non-technical audiences.
- Strong presentation skills.
- Collaborative approach to working across technical and business teams.
- Experience with automotive market data is a strong advantage.
- A PhD in Statistics, Data Science, Economics, or a related field is an additional advantage.
Responsibilities
- Immerse yourself in automotive industry data to uncover patterns, trends, and insights that can improve predictive analytics and support new data products.
- Design, develop, evaluate, optimize, and deploy advanced AI/ML and classical regression models for production use.
- Lead complex end-to-end data science projects, taking ownership from problem definition and feature engineering through modeling, validation, deployment, and ongoing improvement.
- Develop innovative machine learning processes and document methodologies, assumptions, workflows, and results.
- Collaborate closely with technology and engineering teams to improve existing processes and support reliable production deployment.
- Partner with product teams to create analytics and predictive capabilities that power new products.
- Use advanced feature engineering and statistical techniques to improve model performance.
- Leverage Python, R, SQL, Snowflake, and relevant machine learning frameworks.
- Develop visual reports and dashboards in Tableau to communicate findings.
- Conduct ad-hoc data analysis, reporting, and investigations to answer business questions.
View Full Description & ApplyYou'll be redirected to the employer's site
