Principal Data Scientist
1 month ago
Stem provides clean energy solutions and services designed to maximize the economic, environmental, and resiliency value of energy assets and portfolios. Stem’s leading AI-driven enterprise software platform, Athena®, enables organizations to deploy and unlock value from clean energy assets at scale. Powerful applications, including AlsoEnergy’s PowerTrack, simplify and optimize asset management and connect an ecosystem of owners, developers, assets, and markets. Stem also offers integrated partner solutions to help improve returns across energy projects, including storage, solar, and EV fleet charging. For more information, visit .
Stem’s culture embodies diversity & inclusion beyond the traditional facets of gender, ethnicity, age, disabilities, and sexual orientation to include experience, personality, communication, workstyles, and more. At our core, Stem is at the momentous intersection of clean energy and software technology where diverse ideas, experiences, and professional skills converge to make the inclusive culture we have today. Together, we are turning old school thoughts about software and energy into progressive, collaborative, and innovative solutions. By joining our team, you will be collaborating with data scientists, energy experts, skilled salespeople, thought-leading executives and more from a range of backgrounds. This intersection of ideas, beliefs, and skills is what makes us unique enough to lead the world’s largest network of digitally connected energy storage systems.
What we are looking for:
The Data Scientist will be a part of Stem’s machine learning and simulations team and will work on R&D in time series forecasting capabilities at Stem. They will further develop Stem’s state-of-the-art time series forecasting pipeline. This individual will work closely with the Head of Controls and Optimization and cross-functional team members to drive the technical direction of the forecasting capabilities of the Athena platform.
Responsibilities:
R&D in all aspects of time series forecasting products, including domain driven advanced feature engineering and model development.
Implement, validate and productize new features in forecasting product suite.
Collaborate with the operations team in deploying and stabilizing new forecast products and support active production issues.
Partner with business development & product mgmt. to evaluate capabilities in new markets and provide inputs into technology roadmaps.
Collaborate with other data scientists to scale and expand forecasting capabilities.
Participate in agile development processes within the team, and follow high standards for automation, quality and transparency/observability.
Foster a strong technical culture characterized by high-quality implementations, effective organizational communication, decisiveness and speed, constructive conflict resolution, and a can-do mentality.
Establish effective and collaborative cross-functional working relationships with peers, developers, and the product management and operations teams.
Required Experience:
8+ years’ experience in delivering industry-leading software and data science products.
Prior experience in model development & time series forecasting
Prior experience delivering production-grade software in a test-driven environment with a dev-ops mentality.
Experience with agile practices.
Expert knowledge of Python and data science libraries such as numpy and pandas.
Application areas: solar generation forecasting and price forecasting, GenAI & APM Analytics
Energy domain experience and familiarity with wholesale markets and solar + storage applications
Familiarity with Docker, Kubernetes and microservices architecture
Experience with Deep-neural-network architectures and tree-based models used in time series forecasting
Experience with cloud technologies– AWS preferred
Test-driven development: Unit tests, CITs, SITs
Power user of JIRA, Confluence
Experience with CICD tools such as Jenkins, CircleCI, TravisCI, Argo CD.
Algorithm ops: Testing, Validation, Feature engineering, A/B testing
Experience with ML libraries such as scikit-learn and keras.
Qualifications:
M.S. or Ph.D. in Engineering, applied physics or applied mathematics
8 years of experience as a data scientist building state-of-the-art machine learning pipelines.
Extraordinary communication skills, and able to present on complex technical topics to non-technical audiences.
Experience in high-quality companies known for excellence in engineering is highly desirable.
Intellectually curious: You’re interested in understanding and experimenting with new cutting-edge technologies.
Decisiveness: You gather the data and make informed, critical decisions quickly.
Experience in full life cycle agile engineering practices ranging from concept, design, development, and QA to continuous release and maintenance.
An entrepreneurial spirit with an ability to operate successfully in a high-growth company environment.
A positive, energetic, can-do attitude: You’re driven to succeed, achievement-oriented, and self-motivated with high integrity, principles, and ethics.
Work arrangement- Hybrid, Gurgaon
Stem, Inc. is an equal opportunity employer committed to diversity in the workplace and does not discriminate against any employee or applicant for employment because of race, color, sex, pregnancy, religion, national origin, ethnicity, citizenship, sexual orientation, gender identity, age, marital status, disability, genetic information, military status, protected veteran status or any other factor protected by applicable federal, state or local laws.
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