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Salary
$49k – $120k per year (Estimated)
Location
Remote (Spain)
Seniority
Senior · 8+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is a Belgian recruitment platform built entirely around remote and flexible work, aggregating openings from thousands of employers that allow work from outside an office. Its matching engine ranks roles against a candidate's skills, seniority and stated preferences on location and flexibility, rather than leaving people to filter a keyword search, and it verifies how genuinely remote each posting is. The company also runs an AI screening layer that shortlists applicants for employers, and publishes research and guidance on distributed work practices alongside the job marketplace itself.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Spain.

This role offers the opportunity to build advanced data products that solve meaningful problems across the automotive industry.

You will work with large-scale datasets to understand the factors that influence vehicle pricing and predict future market values.

The position combines advanced machine learning, statistical modeling, data engineering, and business-focused analytics.

You will have the freedom to explore modern technologies, develop innovative models from the ground up, and take them through production.

Your work will directly influence core data products and help turn complex industry data into actionable insights.

You will join a mature, collaborative data science team that values curiosity, technical excellence, knowledge sharing, and continuous development.

The environment is well suited to an experienced data scientist who wants meaningful ownership and visible impact.

Accountabilities

    • 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 to ensure that analytical outputs remain accurate, transparent, and reproducible.
    • Collaborate closely with technology and engineering teams to improve existing processes, develop new capabilities, and support reliable production deployment.
    • Partner with product teams to create analytics and predictive capabilities that power new products and address important challenges within the automotive market.
    • Use advanced feature engineering and statistical techniques to improve model performance and uncover meaningful relationships within large datasets.
    • Leverage Python, R, SQL, Snowflake, and relevant machine learning frameworks for advanced data manipulation, modeling, and analysis.
    • Develop visual reports and dashboards in Tableau to communicate findings and analytical outcomes to internal and external audiences.
    • Contribute ideas, technical approaches, and modeling strategies within the data science team while continuously exploring ways to improve predictive algorithms.
    • Conduct ad-hoc data analysis, reporting, and investigations to answer emerging business and product questions.
    • Requirements:

      • Bring at least 8 years of overall professional experience with a Bachelor’s degree, or at least 6 years of experience with a graduate degree, including substantial hands-on data science experience.
      • Have at least 4 years of experience working with large datasets and applying statistical or analytical methods to complex data problems.
      • Have 4+ years of experience with statistical programming and data science tools, with strong Python or Spark experience preferred and R or SAS experience considered a plus.
      • Have at least 4 years of experience working with database technologies such as MS SQL, Snowflake, or MySQL.
      • Demonstrate strong knowledge of machine learning, statistical modeling, advanced feature engineering, model evaluation, and predictive analytics.
      • Have practical experience taking machine learning models into production, ideally including cloud-based MLOps environments and API-based model deployment.
      • Be comfortable working with cloud infrastructure and modern machine learning frameworks, with the ability to build scalable and maintainable analytical solutions.
      • Be able to communicate technical concepts clearly to non-technical audiences and translate complex analytical findings into understandable business insights.
      • Bring strong presentation skills and the ability to share analytical results effectively with colleagues, stakeholders, and clients.
      • Demonstrate curiosity, creativity, and a genuine passion for solving challenging problems through data.
      • Work collaboratively across teams, actively contribute ideas, and build strong working relationships with technical and business stakeholders.
      • Experience with automotive market data, large-scale predictive analytics, or related industry datasets is a strong advantage.
      • Experience using AI assistants such as Claude within machine learning or data science projects is a plus.
      • Shareable examples of data visualizations or analytical work are valued.
      • A PhD in Statistics, Data Science, Economics, or a related field is an additional advantage.
      • Candidates must be legally authorized to work in Spain, as employment sponsorship is not provided for this position.
      • Benefits:

        • Opportunity to work on data products with direct impact on automotive industry decisions and market analytics.
        • Significant ownership over advanced machine learning projects, from initial concept through production deployment.
        • Access to modern technologies and the freedom to explore innovative approaches to data science and machine learning.
        • Collaborative environment with close interaction across data science, engineering, technology, and product teams.
        • Virtual-first working environment with flexible work arrangements.
        • Opportunities for continuous learning, professional development, and growth as both a technical expert and collaborative professional.
        • Culture centered on innovation, collaboration, data-driven decision-making, execution, trust, and accountability.
        • Opportunity to contribute ideas and shape predictive algorithms and analytical products used by internal and external stakeholders.
        • Work within an experienced and established data science team where knowledge sharing and technical excellence are encouraged.
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