Data Scientist – Construction Operations

  • Full Time
  • Anywhere
  • Full Time
  • Anywhere


As Part of the Tesla
infrastructure development team youll be responsible
for gathering data and performing advanced
analytics, creating infrastructure and data pipelines, developing predictive
models and making data applications that enablecross functional teams to
leverage a wealth of construction productivity, scheduling strategy, and
critical path data efficiently. In this role, youwill develop systems and
tools for field technicians, subcontractors, and project managers to visualize
live metrics on construction progress while creating financial and productivity
models to identify potential risks early on.
Moreover, youwillcreate software tools
to support Construction throughout project lifecycles, and
contribute to data platform infrastructure aiding in Teslas goal of
accelerating the worlds transition to sustainable energy


Design and develop data collection tools to track cost and schedule
productivity across Teslas various construction project teams

Develop a multitude of metrics that will be used by
project teams, financial planners and the executive management team

Work with field teams to continuously find
improvements to minimize their time spent on data entry, enabling more
productive time on installations

Engage with cross functional teams to
identify data sources where the potential value is not fully realized and
invent new means with which to interact and gather insights from them


Bachelors degree or higher in quantitative
discipline (e.g. Statistics, Computer Science, Mathematics, Physics, Electrical
Engineering, Industrial Engineering) or the equivalent in experience and
evidence of exceptional ability

3+ years of work experience in data analytics,
data engineering, data science, machine learning or related fields

Knowledge in construction, construction
cost or trade management highly desirable, but not required

Extensive experience writing software with

Experience with multiple data architecture
paradigms (e.g. MySQL, MicrosoftSQL, Oracle, MongoDB, Kafka, Hadoop, Hbase,

Experience withinfrastructure and
continuous integration pipelines (e.g. Docker, Kubernetes, Airflow, Jenkins)

Experience with data visualization
techniques and tools (e.g. Matplotlib, Plotly, Superset, Tableau), quick web
application experience preferred (e.g. Flask, JQuery, Streamlit, Angular 2+)

Knowledge of various data communication
protocols (e.g. REST API, gRPC, Websockets)

Able to work under pressure while
collaborating and managing demanding deadlines

A passion for machine learning, a results-oriented mindset
and appetite to continuously learn and ask questions



Tagged as: Other - Data Science & Analytics

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