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28 Jan 2016

Full-Time Junior Data Scientist @ Chicago, Illinois, United States

DRIVIN – Posted by drivindealer Chicago, Illinois, United States

Job Description

Jr. Data scientist

Location: Chicago, IL Department: Data Analytics

Type: Full Time Min. Experience: Mid Level

 

DRIVIN

  • We are fast-paced, forward thinking and driven by data.
  • We are accelerating the used car industry.
  • We are looking for creative, talented, hard-working individuals to join us.
  • Buckle up. It’s going to be a great ride.

 

Based in Chicago, DRIVIN (a CarCo Technologies company) is accelerating the used car industry by bringing data and technology together in a spectacular, first-of-its-kind fashion to help dealers acquire the right cars, at the right price, right now. We are committed to delivering data-driven solutions with a high-touch, personalized level of service to each of our clients.

 

As a premier venture-backed, rapidly growing start-up, we are looking for world-class individuals to join our team, including creative technologists, forward-thinking sales and marketing professionals, entrepreneurial hackers and data scientists. We are committed to offering our employees top benefits and perks, including medical, dental, vision, 401k, life insurance, tech subsidies, and much more.

 

We are looking for people that will help us create a culture that is exciting, empowering, motivating and challenging. Are you interested in learning more?

 

The Role

At our core, we are an analytics company. The insights we gain from our analyses guide our strategic path forward as we grow revenue, enter new markets, and strengthen our customer relationships. The Analytics team proactively leads and collaborates to identify the most valuable problems to solve, constructs a Roadmap to delivery, and executes our plan. The Data Scientist role will have both autonomy and accountability when constructing the problems to solve as well as their solutions, all while working with cross-functional teams to ensure we are delivering the best data insights possible to both internal stakeholders and customers alike.

 

The Responsibilities

  • Develop and maintain 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 to structure problems and understand the impact across various departments within the company

 

The Requirements

  • Minimum of a Bachelor’s Degree in a quantitative field with 1 to 3 years of experience. If you can tell a story related to how you can leverage your educational background on a data science team, we are all ears
  • Experience designing and implementing a broad range of Regression techniques
  • Experience designing and implementing Machine Learning models (preferable)
  • Experience coding with R, Python, and SQL languages
  • Familiarity with Spark and Amazon Web Services (preferable)
  • Ability to clearly explain findings from complex analyses in case studies and power point
  • Be a collaborative teammate, sharing knowledge and learning from others while working through complex problems
  • Confidence, hustle, energy, and drive – accountability is key and the impact of your work is crucial to our success
  • You are always ready for the next challenge, always one step ahead, looking for creative ways to improve upon processes

How to apply: Please apply on www.carcotech.com OR email [email protected]

How to Apply

Please apply on www.carcotech.com OR email [email protected]

Job Categories: Data Scientist / Statistician. Job Types: Full-Time. Salaries: Less than $100,000.

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