● Work with large, complex datasets of various vehicular subsystems; solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverable and presentations.
● Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of vehicular systems and data and offer security-focused insights regarding anomalies in the data sets.
● B.Sc. degree in a quantitative discipline (e.g., statistics, bioinformatics, economics, computer science, mathematics, physics, electrical engineering, industrial engineering) or equivalent practical experience.
● 5 years of relevant work experience in data analysis or related field (e.g., as a statistician / data scientist).
● Experience with statistical software (e.g., R, Python, MATLAB) and database languages (e.g., SQL).
● Independent self-starter and team player
● Passionate about constantly learning new skills in a fast-paced environment
● M.Sc/PhD degree in a quantitative discipline
● 8 years of directly relevant, tech industry work experience, including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, deep learning, Bayesian inference.
● Applied experience with machine learning and deep learning on very large data sets.
● Experience articulating cyber security goals and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into actionable information.
● Demonstrated skills in selecting the right statistical tools given a data analysis problem. Demonstrated effective written and verbal communication skills.
● Competitive Programmer or Competitive Data Scientist
● Knowledge of scalable data visualization techniques
● Ability to create prototypes quickly