Analyze large-scale datasets from various sources, such as fleet and simulation data, to extract actionable insights.
Develop and evaluate novel algorithms and methodologies for data processing, feature engineering, model training, and performance optimization.
Evaluate and validate model performance through rigorous testing and analysis, ensuring the safety and reliability of our systems.
Communicate complex technical findings and recommendations to both technical and non-technical audiences.
Mentor and provide technical guidance to junior data scientists and engineers.

Requirements

Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with 8+ years of experience as a Data Scientist.
Strong programming skills in Python, including experience with relevant libraries such as scikit-learn, and Pandas & SQL.
Expertise in a wide range of machine learning techniques, including deep learning, reinforcement learning, and statistical modeling.
Experience working with large-scale datasets and distributed computing platforms (e.g., Spark, Hadoop) with solid understanding of data processing, feature engineering, and data visualization techniques.
Strong communication and presentation skills, with the ability to effectively convey technical information to diverse audiences.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythonscikit-learnPandasSQLmachine learningdeep learningreinforcement learningstatistical modelingdata processingfeature engineering

Soft Skills

communicationpresentationmentoringtechnical guidance

Certifications

Master's degreePh.D.