Staff Data Scientist - Forecasting

over 1 year ago
Full time role
Remote · San Francisco, CA, US... more
Remote · San Francisco, CA, US... more

Company

SPAN is developing products to enable rapid adoption of renewable energy and deliver an intuitive interface for the home. We ...

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Job Description

The Mission

The electrical grid was built to carry electricity unidirectionally from central fossil fuel plants to end consumers. As we transition to a renewable future built from rooftop solar and community storage, the grid itself needs an overhaul. Span’s goal is to reinvent the grid from a clean slate to enable that transition, envisioning a grid made of distributed control systems and software as much as copper wires.

To accomplish this, we are upgrading the breaker panel — the humble box sitting at the center of every building’s electrical wiring — to monitor, control, and make decisions about energy. This converts buildings from passive consumers in a centralized fossil fuel grid to active participants in the emerging distributed energy market.

SPAN’s unique commitment to clean-slate “right architecture” and our zealotry for top-caliber customer experience position us as domain leaders in envisioning the distributed grid and have allowed us to achieve rapid growth and high visibility in the industry in the two years since we launched.

The Role

We aim to establish the SPAN panel as the center of home energy and the backbone of the renewable distributed grid. Analytics and ML are essential tools to develop features for the smart, green, energy-efficient home of the future. SPANn’s unique ability to monitor and control individual circuits opens up a new avenue for proactive whole-home management and equipment failure detection. As Data Scientist, you will leverage your deep understanding of ML, modeling, and statistics to solve problems including anomaly detection, time series forecasting, and event prediction with the goal to optimally manage whole-home energy consumption, deliver meaningful insights to the customer, and notify them about a potential failure of equipment or hazards in their home. You’ll be involved through the entire development process, from the acquisition of all additional third-party data, the initial design to remote monitoring in the field.

 

Responsibilities

Lead the development of ML algorithms from the ground up which includes:

  • Gain knowledge in the relevant domain (e.g. energy consumption pattern of homes)

  • Feature engineering

  • Prototype new algorithms

  • Benchmark performance across large-scale datasets

  • Use your experience with different machine learning frameworks to identify suitable tools for integration in SPAN’s software platform

  • Integrate developed algorithms in our production code base with robust test coverage

  • Work with the firmware and software teams to design Span’s edge model deployment framework; pick which ML framework SPAN should adopt

  • Proactively identify opportunities within Span that can benefit from data science analysis

  • Use fleet data to monitor algorithms in the field

Note: We’re a startup, so while this list is broad, it’s still just a start; you’ll end up wearing many hats during your time at Span.

About You

Required Qualifications
  • Bachelor’s degree or higher in Computer Science, Mathematics, Engineering, or a closely related field

  • 2+ years of professional experience with developing and implementing machine learning models to production

  • Deep understanding of machine learning algorithms for time series data forecasting

  • Advanced Python skills, as well as familiarity with pandas and scikit-learn

  • Software design experience and ability to write clean, maintainable, and shippable production code

  • Experience working with SQL and data visualization tools

  • Extensive data modeling and data architecture skills

  • Knowledge and experience working within cloud computing environments such as AWS

  • Strong communication and interpersonal skills

  • Ability to understand and explain complex problems simply and effectively

Bonus Qualifications
  • Experience optimizing models for resource-constrained edge devices

  • Experience in data engineering

  • Domain-specific knowledge either through previous work, courses in college, or side projects

The U.S. base salary range for this position is $134,000 - $183,000 plus benefits, equity and variable compensation for Sales-related roles. This range represents SPAN’s good faith estimate of competitively-priced salary for the role based on national, real-time industry data from companies of a similar growth stage. This range reflects minimum and maximum new hire salaries for the role across US locations. Within the range, individual pay is determined by location and individual factors including relevant skills, experience and education or training. This range correlates to the relative level of the candidate we believe we need for the role and may require an adjustment for candidates of a different level. 

Your recruiter can share more about the specific salary range for the location this role is based during the hiring process. 
 

Life at SPAN

SPAN embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. 

Headquartered in San Francisco’s vibrant SoMa neighborhood, we are an eclectic group of creative thinkers who value open communication, teamwork, and a ‘make it happen’ approach to addressing complex challenges. 

We’re hiring talented individuals who are driven by success and are passionate about shaping the future of renewable energy. If that sounds like you, we’d love for you to consider joining the rapidly growing team at SPAN.

The Perks:

⚡ Competitive compensation + equity grants at a well-funded, venture-backed company

⚡ Comprehensive benefits (including medical; dental, vision, life and disability insurance)

⚡ Comfortable, sunny office space located near BART and Caltrain public transit

⚡ Strong focus on teambuilding and company culture (events, meet-ups, clubs)

⚡ Flexible hours and unlimited PTO

Interested in joining our team? Submit an application today and we’ll be in touch with next steps!

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