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    [title] => Data Scientist 
    [content] => <div>Ridecell (<a href="http://www.ridecell.com/" target="_blank" data-saferedirecturl="https://www.google.com/url?hl=en&amp;q=http://www.ridecell.com/&amp;source=gmail&amp;ust=1515706006625000&amp;usg=AFQjCNGkRZEoNmaubmc7oBqNz5JXpGMO5g">www.ridecell.com</a>) is powering next generation of ridesharing, carsharing and autonomous new mobility services. As the world shifts to a mobility on-demand model and new companies rush to enter as service providers, Ridecell is ready to support these initiatives. Already 20 customers, including BMW, VW, Renault and AAA use our proven platform to launch, operate, and scale their new mobility services.</div>
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<div>We are looking for someone to work with the data team and internal clients to build/provide the next level platform for analytics and machine learning.</div>
<div> </div>
<h3>Responsibilities </h3>
<div>
<ul>
<li>Recommendations on database infrastructure and data pipeline in order to ensure that necessary data is available for both analytic and machine learning environments.</li>
<li>Determine the best algorithms to apply to the data, including machine learning tools as appropriate.</li>
<li>Collaborate with development engineers to incorporate your models and insights into deployed products.</li>
</ul>
</div>
<div> </div>
<h3>Requirements </h3>
<div>
<ul>
<li>BS, MS or PhD in Statistics, Computer Science, Data Science or a related field.</li>
<li>Extensive experience working with various data sets, knowledge of state of the art in machine learning, and understanding of the power and shortcomings of data</li>
<li>Experience using TensorFlow or other large scale machine learning frameworks in production</li>
<li>Extensive experience with BI tools and the knowledge to work with internal clients to ultimately determine the best fit for our organization.</li>
<li>Experience working with Hadoop, Spark and other tools for distributed computing is essential.</li>
</ul>
</div>
<div> </div>
<div>
<h3>Preferred </h3>
<ul>
<li>Experience with best practices in data security, integrity, workflow traceability, and auditing</li>
<li>Experience with optimization and statistical data analysis tools</li>
<li>Experience with one or more programming languages (Python, R, etc)</li>
<li>Experience with cloud (non-hosted) environments, their tools, their pros and cons</li>
<li>Your experience has been in the context of an early stage effort. This could be at a startup or a new project in a more established company.</li>
<li>Comfortable working as part of a cross-functional team with shifting priorities as needs change and new opportunities arise.</li>
<li>Experience with software engineering concepts in a small, tightly coupled team--and how these evolve with growth of the team</li>
<li>Deadlines are your friend, and you’re a natural communicator who can articulate bottlenecks and challenges.</li>
<li>Outstanding technical leadership and communication skills</li>
<li>Innate curiosity leads you to keep up with the latest research, news and developments in your field.</li>
<li>If you’ve published journal articles, conference papers or technical reports, that’s a plus. We expect you to share the insights, best practices and paths forward that you develop with the rest of the world, including at relevant industry conferences.</li>
<li>Logistic regression, decision trees, SVM etc</li>
<li>Neural nets / deep learning</li>
<li>Clustering algorithms and their applications</li>
<li>Predictive modeling</li>
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Data Scientist

At Ridecell View All Jobs
San Francisco, CA

Ridecell (www.ridecell.com) is powering next generation of ridesharing, carsharing and autonomous new mobility services. As the world shifts to a mobility on-demand model and new companies rush to enter as service providers, Ridecell is ready to support these initiatives. Already 20 customers, including BMW, VW, Renault and AAA use our proven platform to launch, operate, and scale their new mobility services.
 
We are looking for someone to work with the data team and internal clients to build/provide the next level platform for analytics and machine learning.
 

Responsibilities 

  • Recommendations on database infrastructure and data pipeline in order to ensure that necessary data is available for both analytic and machine learning environments.
  • Determine the best algorithms to apply to the data, including machine learning tools as appropriate.
  • Collaborate with development engineers to incorporate your models and insights into deployed products.
 

Requirements 

  • BS, MS or PhD in Statistics, Computer Science, Data Science or a related field.
  • Extensive experience working with various data sets, knowledge of state of the art in machine learning, and understanding of the power and shortcomings of data
  • Experience using TensorFlow or other large scale machine learning frameworks in production
  • Extensive experience with BI tools and the knowledge to work with internal clients to ultimately determine the best fit for our organization.
  • Experience working with Hadoop, Spark and other tools for distributed computing is essential.
 

Preferred 

  • Experience with best practices in data security, integrity, workflow traceability, and auditing
  • Experience with optimization and statistical data analysis tools
  • Experience with one or more programming languages (Python, R, etc)
  • Experience with cloud (non-hosted) environments, their tools, their pros and cons
  • Your experience has been in the context of an early stage effort. This could be at a startup or a new project in a more established company.
  • Comfortable working as part of a cross-functional team with shifting priorities as needs change and new opportunities arise.
  • Experience with software engineering concepts in a small, tightly coupled team--and how these evolve with growth of the team
  • Deadlines are your friend, and you’re a natural communicator who can articulate bottlenecks and challenges.
  • Outstanding technical leadership and communication skills
  • Innate curiosity leads you to keep up with the latest research, news and developments in your field.
  • If you’ve published journal articles, conference papers or technical reports, that’s a plus. We expect you to share the insights, best practices and paths forward that you develop with the rest of the world, including at relevant industry conferences.
  • Logistic regression, decision trees, SVM etc
  • Neural nets / deep learning
  • Clustering algorithms and their applications
  • Predictive modeling

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