Data Scientist - Forecasting
San Francisco
Span.IO, Inc.
SPAN creates smart products designed to make your home more energy efficientThe 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:
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Gain knowledge in the relevant domain (e.g. energy consumption pattern of homes)
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Feature engineering
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Prototype new algorithms
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Benchmark performance across large-scale datasets
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Use your experience with different machine learning frameworks to identify suitable tools for integration in SPAN’s software platform
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Integrate developed algorithms in our production code base with robust test coverage
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Work with the firmware and software teams to design Span’s edge model deployment framework; pick which ML framework SPAN should adopt
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Proactively identify opportunities within Span that can benefit from data science analysis
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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
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Bachelor’s degree or higher in Computer Science, Mathematics, Engineering, or a closely related field
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2+ years of professional experience with developing and implementing machine learning models to production
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Deep understanding of machine learning algorithms for time series data forecasting
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Advanced Python skills, as well as familiarity with pandas and scikit-learn
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Software design experience and ability to write clean, maintainable, and shippable production code
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Experience working with SQL and data visualization tools
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Extensive data modeling and data architecture skills
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Knowledge and experience working within cloud computing environments such as AWS
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Strong communication and interpersonal skills
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Ability to understand and explain complex problems simply and effectively
Bonus Qualifications
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Experience optimizing models for resource-constrained edge devices
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Experience in data engineering
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Domain-specific knowledge either through previous work, courses in college, or side projects
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.
Our CEO, Arch Rao—former head of the Tesla Powerwall team—fosters an energetic and collaborative environment, with a strong emphasis on maintaining work-life-balance across the organization.
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 team building and company culture (events, meet-ups, clubs)
⚡ Flexible hours and unlimited PTO
Our Mission & Values:
At SPAN, we believe that powering your home with clean energy should be a simple and delightful experience that is at its essence human-centered and technology-forward.
Our core values include:
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Making home energy more accessible, intuitive, and convenient.
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Enabling homes and vehicles to be powered by the sun.
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Building resilient homes with reliable power.
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All-electric everything.
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A more flexible & distributed grid.
Interested in joining our team? Submit an application today and we’ll be in touch with the next steps!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Computer Science Data visualization Engineering Feature engineering Machine Learning Mathematics ML models Model deployment Pandas Python Scikit-learn SQL Statistics
Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Health care Insurance Salary bonus Startup environment Team events Unlimited paid time off
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