Data science Team leader
SafeRide
Bochum, DE
vor 6 Tg.
  • Manage a team of data science, support the existing team and grow the team
  • Work with internal and external subject matter experts to drive the product’s roadmap, execution plan and milestones
  • Provide day to day guidance and assistance to team members to successfully deliver the product
  • Participate actively in implementing complex algorithms
  • Drive complex multi-disciplinary project under demanding time frames in complex customer environments
  • 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.



  • PhD degree in a quantitative discipline (e.g., statistics, bioinformatics, economics, computer science, mathematics, physics, electrical engineering, industrial engineering) or equivalent practical experience.

●     8-10 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.

●  3 years of managerial experience

● 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

●     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.


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