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Data Scientist
The Reynolds and Reynolds Company
- United States
- United States
À propos
The Appraisal Lane is a real-time used car trade network and communications platform. It enables dealers to submit used cars for appraisal and receive cash offers from a network of experts who balance knowledge with market valuation data resulting in the most accurate used car valuations. Fully optimized for mobile, the platform manages appraisal submissions, purchase offers, and dealer, appraiser, and buyer communications, as well as sales and fulfillment channel information. All of this is possible thanks to our team of experts. The TAL engineering team works in constant collaboration while enjoying their work and company... because when you love what you do it shows. Teamwork, collaboration, leadership, camaraderie… these are the values upon which our work is founded. We want people who share them and are willing to come on board and help us in our continued growth. Based in Austin, US, and Montevideo, UY, TAL is accelerating the used car industry by bringing data and technology together in an innovative way to help dealers acquire the cars they want, when they want them and at the price they want. We believe in creating a partnership based on the delivery of data-driven solutions while maintaining a personalized service in each transaction. What You'll Do
Develop predictive modeling and machine learning solutions that continually improve with the collection of real-time customer results from the marketplace. Execute demand-based modeling, utilizing industry supply and demand data along with consumer shopping behaviors/trends. Work in an Agile environment with team members, delivering interim solutions quickly and continuously exploring ways to improve our results. Actively seek out new potential problems to solve, building out our future Roadmap while simultaneously executing our present analyses. Work closely with colleagues in Product, Operations, and Sales. Requirements
Strong background in Algebra, Calculus and Statistics - minimum of a Bachelor's Degree in any of these fields. Knowledge of common Machine Learning algorithms and processes. Experience with previous Data Science/Machine Learning/AI projects. Advanced Experience coding with Python or R, and SQL languages. Knowledge of multi use ML libraries like: numpy, scipy, scikit-learn, matplotlib, pandas. Experience designing and implementing a broad range of Regression techniques. It will be taken into account but not required, knowledge on Theano, Tensor Flow or similar Neural Net python libraries. Strong problem solving and analytical skills Good verbal and written communication skills in English. Able to work full-time—8 hours per day. Highly motivated and avid for new challenges. Eager to take part in the growth of an exciting new company. Looking forward to participate in the development and testing of cutting edge products. The System Our system consists of many micro-services; the core of our platform is the backend API, which drives the behavior of our mobile and web clients. A few specific aspects of our core system are: Web-Socket support for real time updates on the clients. Ruby on Rails, Python/Flask and Nodejs based modules. Python powered statistics system (numpy, pandas, scipy). noSQL databases (redis, elasticsearch/lucene). Our web client is fully written on angular-js and is architected using the latest design paradigms (component based design). We have both native Android and iOS apps built with: Local data storage Complex data sync mechanism with the core system. Full duplex communication via Web-Sockets Dynamic form generation and validation using a jSON based structure with defined rules Real time messaging and UI updates
Compétences linguistiques
- English
Avis aux utilisateurs
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