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    [updated_at] => 2020-01-27T20:17:36-05:00
    [requisition_id] => 246
    [title] => Data Scientist, Scenario Modeling
    [content] => <h1><span style="font-weight: 400;">Data Scientist, Scenario Modeling</span></h1>
<p><span style="font-weight: 400;">The complexity of urban driving stems from the large number of scenarios that may need to be handled. Understanding the space of these scenarios is a critical phase in designing planners and decision-making modules. And the ability to reproduce scenario variations in simulation allows us to train, test and validate our autonomous driving systems in a comprehensive manner.</span></p>
<p><span style="font-weight: 400;">If you're passionate about autonomous vehicles, and believe in modeling as an effective means of capturing the dynamics of driving scenarios, join us today!</span></p>
<h2><span style="font-weight: 400;">What You'll Do</span></h2>
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<li style="font-weight: 400;"><span style="font-weight: 400;">Research existing approaches to scenario modeling and abstraction.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Develop data collection and processing pipeline for scenario mining.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Design and improve models to better capture scenario dynamics.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Define taxonomy of scenario elements and their relationships.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Develop a metadata tagging scheme based on a taxonomy.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Extract scenarios, events &amp; relationships from recorded data.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Learn parameter distributions from recorded data.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Explore graph-based/probabilistic matching techniques.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Derive concrete scenarios for execution in simulation.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Work closely with traffic/actor modeling initiatives to reproduce natural actor behavior.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Disseminate scenario modeling results through talks, workshops, and conference papers.</span></li>
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<h2><span style="font-weight: 400;">Desired Qualifications</span></h2>
<ul>
<li style="font-weight: 400;"><span style="font-weight: 400;">Masters or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">5+ years research experience modeling real-world phenomena using a combination of mathematical abstractions, probability distributions and/or logical formalisms.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Proficiency in data analysis, data visualization, model definition and model fitting.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Proficiency in using numeric and scientific computing tools and libraries.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with modeling spatial data such as vector maps, geospatial distributions.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with modeling temporal data such as time series, streams and events.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with modeling graph/network data.</span></li>
</ul>
<h2><span style="font-weight: 400;">Nice to Have</span></h2>
<ul>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with modeling macroscopic traffic behavior.</span></li>
<li style="font-weight: 400;"><span style="font-weight: 400;">Experience with modeling microscopic vehicle or pedestrian motion.</span></li>
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Data Scientist, Scenario Modeling

At Ridecell View All Jobs
Milpitas

Data Scientist, Scenario Modeling

The complexity of urban driving stems from the large number of scenarios that may need to be handled. Understanding the space of these scenarios is a critical phase in designing planners and decision-making modules. And the ability to reproduce scenario variations in simulation allows us to train, test and validate our autonomous driving systems in a comprehensive manner.

If you're passionate about autonomous vehicles, and believe in modeling as an effective means of capturing the dynamics of driving scenarios, join us today!

What You'll Do

  • Research existing approaches to scenario modeling and abstraction.
  • Develop data collection and processing pipeline for scenario mining.
  • Design and improve models to better capture scenario dynamics.
  • Define taxonomy of scenario elements and their relationships.
  • Develop a metadata tagging scheme based on a taxonomy.
  • Extract scenarios, events & relationships from recorded data.
  • Learn parameter distributions from recorded data.
  • Explore graph-based/probabilistic matching techniques.
  • Derive concrete scenarios for execution in simulation.
  • Work closely with traffic/actor modeling initiatives to reproduce natural actor behavior.
  • Disseminate scenario modeling results through talks, workshops, and conference papers.

Desired Qualifications

  • Masters or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
  • 5+ years research experience modeling real-world phenomena using a combination of mathematical abstractions, probability distributions and/or logical formalisms.
  • Proficiency in data analysis, data visualization, model definition and model fitting.
  • Proficiency in using numeric and scientific computing tools and libraries.
  • Experience with modeling spatial data such as vector maps, geospatial distributions.
  • Experience with modeling temporal data such as time series, streams and events.
  • Experience with modeling graph/network data.

Nice to Have

  • Experience with modeling macroscopic traffic behavior.
  • Experience with modeling microscopic vehicle or pedestrian motion.

Apply for the job

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