● Work as part of the data science team, support the existing team and grow with them.
● Work with internal and external subject matter experts to drive the product’s road map, execution plan and milestones
● Participate actively in implementing complex algorithms
● 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 deliverables 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.
● BA degree in a quantitative discipline (e.g., statistics, bioinformatics, economics, computer science, mathematics, physics, electrical engineering, industrial engineering) or equivalent practical experience.
● 1-2 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
● MSc or PhD student in a quantitative discipline
● 1-2 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 datasets.
● Experience articulating cybersecurity 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.