Dash Job - Intermediate Data Scientist 2, Visualization - Pacific Northwest National Laboratory

:mega: Plotly Dash Skills: The candidate will have experience with packages for creating visualizations for the data science workflow such as Plotly Dash

Company: Pacific Northwest National Laboratory

Title: Intermediate Data Scientist 2, Visualization

Category: Full Time

Location: United States (Remote)

Experience: Entry-Mid level

Application: Link to apply


We’re a team of visual analytics researchers who love making big, complex data useful through new computational methods, great visual design, compelling interaction, support for sound analytic technique, novel human- machine teaming, and solid engineering. We develop new ways for people to benefit from data and care deeply about the intersection between human and computer to solve problems in new ways. We work with partners across PNNL to create solutions for our customers’ hardest analysis challenges.

This position is for an early career researcher who is passionate about innovating at the intersections of visualization, HCI, and machine learning. The researcher will contribute to teams that develop innovative visual analytics prototypes that address challenges across a wide set of national security application domains. The researcher is encouraged to interact with the international visualization community, publishing in and attending conferences including but not limited to IEEE VIS, ACM CHI, ACM IUI.

National Interest Project Examples

  • Detect and prevent smuggling of drugs and contraband at ports of entry
  • Develop large data pipelines to thwart funding for terrorists, nuclear proliferators, drug cartels, and rogue leaders
  • Applying big data solutions to national security problems
  • Applying image classification for nuclear forensics analysis
  • Detect and respond to advanced cyber threats with at-edge computing
  • Develop capabilities for scalable geospatial analytics
  • Use remotely sensed imagery to identify and monitor the progression of wildfires
  • Analyze the resiliency of the electric power grid to prevent large-scale outages
  • Optimize building efficiency using IOT and ICS data with automated demand-response markets
  • Model climate change and impacts to civilization
  • Hunt for the existence of dark matter to understand the nature of the universe

How We Work

  • Diverse and flexible projects – Flexibility to choose and move between projects
  • Partners – Work with government, academic, industry, and other partners to solve problems
  • Locations – Seattle, WA; Richland, WA; Washington, DC
  • Team Sizes – Typically around 5-10 members, although projects can be more than 100 or just a few members
  • Team Compositions – Our teams include data scientists, domain scientists and engineers, users, and a range of engineering talent from cloud and machine learning engineers to front-end dev

The researcher is expected to work side-by-side with other scientists and engineers to apply advanced theories, methods, algorithms, models, evaluation tools and testbeds, and computational-based solutions to address complex scientific challenges affecting areas such as energy, biological sciences, the environment, and national security.

  • Establishing a local reputation with specialization in at least one S&E domain.
  • Selects and develops technical approaches on assignments with occasional oversight.
  • Beginning to establish a leadership role in professional community including professional societies, other laboratories, academia, and industry.

Minimum Qualifications

  • BS/BA and 2 years of relevant experience -OR-
  • MS/MA -OR-
  • PhD

Preferred Qualifications

  • The desired candidate is a visualization practitioner with experience applying standard visualizations and creating novel visualizations for data analytics.
    • The candidate will have experience with packages for creating visualizations for the data science workflow, e.g. Matplotlib, Seaborn, and Plotly Dash
    • The candidate is gaining experience in modern front-end frameworks, i.e. React.js
    • The candidate is gaining experience with user experience design and evaluation methodologies (e.g, design of experiments, empirical studies, qualitative studies, statistical analysis).
  • The desired candidate is a data science practitioner who selects and widely applies principles, theories and concepts from data science and machine learning to gain insight across a variety of application domains.
    • The candidate has in-depth knowledge in areas such as feature engineering, text analysis, network analysis & visualization, data science, machine learning, and optimization
    • The candidate will be familiar with data science, machine learning, and analytics packages such as Pandas, scipy, scikit-learn, Keras, etc.
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