Full-Time Data Scientist

We're looking for a creative Data Scientist to join Experian Automotive and shape the future of data-driven decision-making.

You'll have opportunity to:

• Build scalable data ecosystems to power advanced analytics, predictive modeling, and thoughtful decision-making.
• Lead forecasting and scenario modeling by integrating dynamic inputs, validating assumptions, and delivering forward-looking insights that anticipate risks and opportunities.
• Automate analytical workflows to accelerate speed-to-insight and reduce manual intervention.
• Use large-scale structured and unstructured data to uncover patterns, create relevant insights, and develop predictive and prescriptive models.
• Design, deploy, and operationalize advanced machine learning solutions.
• Maintain model development pipelines while driving proof-of-concept programs and rapid experimentation.
• Partner with teams to define high-impact use cases and embed data science solutions into strategic decision-making.
• Establish scalable data and model governance practices to ensure reliability, transparency, and continuous improvement.
• Use modern analytics and cloud platforms (e.g., Python, AWS, Databricks, or Tableau) to find the latest solutions.
• Improve algorithmic innovation by refining data analysis techniques, expanding pattern analytics, and generalizing methods for broader data flow coverage.
• Develop intuitive data visualizations and interactive tools to communicate complex insights and increase adoption across the organization.

Education: Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
Technical Expertise: Proficiency in Python and experience with machine learning frameworks; familiarity with SQL and statistical tools.
AI & Advanced Modeling: Hands-on experience with generative AI tools, large language models (LLMs), and advanced machine learning techniques.
Cloud & Deployment: Ability to deploy and scale models in production using cloud platforms (AWS, GCP, Azure) and tools like Databricks; experience with AWS services.
Data Mastery: Experienced in analyzing complex datasets and developing predictive models, experimental designs, and analytic plans to uncover insights and determine causal relationships.
Statistical: Understanding of statistical modeling, forecasting, and performance optimization for machine learning algorithms.
Collaboration & Communication: Ability to translate complex technical concepts into clear, relevant insights for diverse team members.
Innovation and Execution: Experience managing projects end-to-end, delivering impactful solutions.

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