Data Science Engineer
Based in Stamford, Connecticut, RxSpeed Inc. is a venture-backed startup developing software for the automotive aftermarket. If you know someone who has modified the look or performance of their vehicle, we serve companies within the $40 billion annual auto parts industry commonly known as SEMA.
RxSpeed is looking for a Data Scientist with Machine Learning experience. They will lead development and execution of highly complex algorithms and statistical predictive models to determine analytical approaches along with modeling techniques within the automotive industry. Lead and develop highly scalable classifiers and tools leveraging machine learning, data regressions, and rules based models.
- The ideal candidate is smart and savvy in both business and technology.
- Excellent communication skills and has a logical mind
- Establishes analytical rigor and statistical methods to analyze large amounts of data, using advanced statistical techniques and mathematical analyses.
- Defined repeatable analytics delivery model with proven industry methodologies and tools.
- Anticipates and solves strategic and high risk business problems with broad impact on the business area by applying leading-edge theories and techniques to investigate problems, detect patterns and recommend solutions.
- Provides guidance to develop enterprise-wide analytics strategy and roadmap.
- Experience with scripting languages such as PHP, filesystem, server architecture, MySQL, NoSQL.
- 3 + years related experience in one or more of the following areas: machine learning recommendation systems, patterns recognition, data mining or artificial intelligence.
- Bachelor’s or Master's degree in Statistics, Applied Math, Computer Science, or related quantitative discipline is preferred.
Position - Location - Compensation
- If Candidate is Local - 2-3 days a week at 700 Canal Street, Stamford, CT
- If Remote - 5 days a month in Stamford, all expenses paid. (Quick train into NYC for a fun weekend ;)
- Compensation - dependent on your experience.