Full-Time Data Scientist

We’re looking for an innovative Data Scientist to join Experian Automotive and shape the future of data-driven decision-making. In this role, you’ll design and implement advanced analytics solutions, standardize and automate data processes, and develop sophisticated statistical, machine learning, and forecasting models that power business intelligence and client insights. You’ll craft next-generation algorithms, build intuitive data visualization tools, and leverage emerging technologies—including generative AI and advanced modeling techniques—to solve high-impact challenges. Collaborating across Finance, Product, Operations, and Technology teams, you’ll drive automation, optimize analytical workflows, and deliver actionable insights that influence strategic decisions. This is an opportunity to push boundaries, transform data into intelligence, and accelerate innovation across the organization.

• Build and optimize scalable data ecosystems to power advanced analytics, predictive modeling, and intelligent decision-making.
• Lead forecasting and scenario modeling by integrating dynamic inputs, validating assumptions, and delivering forward-looking insights that anticipate risks and opportunities.
• Automate and streamline analytical workflows to accelerate speed-to-insight and reduce manual intervention.
• Leverage large-scale structured and unstructured data to uncover patterns, generate actionable insights, and develop predictive and prescriptive models.
• Design, deploy, and operationalize advanced machine learning solutions—including deep learning, graph-based models, and reinforcement learning—to solve complex business and customer challenges.
• Enhance and maintain model development pipelines while driving proof-of-concept initiatives and rapid experimentation.
• Partner with cross-functional teams to define high-impact use cases, align on priorities, and embed data science solutions into strategic decision-making.
• Establish scalable data and model governance practices to ensure reliability, transparency, and continuous improvement.
• Utilize modern analytics and cloud platforms (e.g., Python, AWS, Databricks, Tableau) to deliver cutting-edge solutions.
• Advance 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 effectively and drive adoption across the organization.

Requirements:Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.

• Strong proficiency in Python and experience with machine learning frameworks such as scikit-learn, XGBoost, or PyTorch; familiarity with SQL and statistical tools (e.g., R, SAS, MATLAB) is a plus.
• Hands-on experience with generative AI tools, large language models (LLMs), and advanced machine learning techniques including supervised, unsupervised, and time-series modeling.
• Proven ability to deploy and scale models in production using cloud platforms (AWS, GCP, Azure) and tools like Databricks; experience with AWS services such as S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2 is highly desirable.
• Data Mastery: Skilled in analyzing large, complex datasets and developing predictive models, experimental designs, and robust analytic plans to uncover insights and determine causal relationships.
• Statistical Acumen: Deep understanding of statistical modeling, forecasting, and performance optimization for machine learning algorithms.
• Collaboration & Communication: Ability to translate complex technical concepts into clear, actionable insights for diverse stakeholders; strong interpersonal skills for cross-functional collaboration.
• Innovation & Execution: Self-motivated, results-driven professional with a track record of managing projects end-to-end, delivering impactful solutions, and meeting deadlines in fast-paced environments.

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