Software Engineer / Data Scientist (Access Controls)


Data is deeply embedded in the product and
engineering culture at Tesla. We rely on data – lots of it – to improve
autopilot, to optimize hardware designs, to proactively detect faults, and to
optimize load on the electrical grid. We collect data from each of our cars,
superchargers, and stationary batteries and use it to make these products
better and our customers safer.

We’re the Fleet Analytics team, a small but
fast-growing central team that helps many teams leverage the data we collect.
We help engineers through direct support by doing data analysis for them and
through applications and tools so they can self-serve those analyses in the
future. To do so, we leverage the internal big data platform that is built on
top of AWS, S3, Spark, Presto and data science tools such as Jupyter notebooks,
Pandas, Bokeh, Superset and Airflow.

We’re looking for a talented engineer to join
us in providing leadership in the definition and implementation of processes
and tools to enable data science at Tesla. Your work will affect many hundreds
of Tesla engineers daily, as well as improving the functionality of our cars,
chargers, and batteries worldwide.

Half your time will be dedicated to hands-on
data analysis for the Access Controls team, while other half will be spent
building data pipelines, tools and applications to automate those analysis. You
will be working closely with integration engineers and firmware engineers to
understand various sensors (for example cameras, radars, and ultrasonics),
wireless technologies (for example, BLE, UWB and NFC), and algorithms utilizing
those sensors and wireless technologies. You will use that knowledge and your
data expertise to understand how customers use their cars, how the sensors and
wireless endpoints behave in a plethora of real world situations, so we can
provide the most seamless and secure passive entry experience to our customers.
Your analysis will also help inform next generation vehicle hardware and
software designs.


  • Work with stakeholders to take a vague problem
    statement, refine the scope of the analysis, and use the results to drive
    informed decisions
  • Write reproducible data analysis
    over petabytes of data using cutting-edge open source
  • Summarize and clearly communicate data analysis assumptions
    and results
  • Build data pipelines to promote your ad-hoc data
    analyses into production dashboards that engineers can rely on
  • Design and implement metrics, applications and tools
    that will enable engineers by allowing them to self-serve their data insights
  • Work with engineers to drive usage of your applications
    and tools
  • Write clean and tested code that can be maintained and
    extended by other software engineers
  • Operate and support your production applications
  • Keep up to date on relevant technologies and
    frameworks, and propose new ones that the team could leverage
  • Identify trends, invent new ways of looking
    at data, and get creative in order to drive improvements in both
    existing and future products
  • Give talks, contribute to open source projects, and
    advance data science on a global scale


  • Strong proficiency in Python, SQL
  • Strong foundation in statistics
  • Experience building data visualizations
  • Experience writing software in a professional
  • Strong verbal and written communication skills
  • Strong problem-solving skills to help refine problem
    statements and figure out how to solve them with the available data
  • Curious and driven to solve complex problems
  • Smart but humble, with a bias for action

to have

  • Experience with data science tools such as Pandas,
    Numpy, R, Matlab, Octave
  • Experience building data pipelines
  • Experience building web applications
  • Experience building machine learning models in a
    professional environment
  • Experience with continuous integration and continuous
  • Experience in devops, i.e. Linux, Ansible, Docker,
  • Understanding of distributed computing, i.e. how HDFS,
    Spark and Presto work
  • Proficient in Scala