Head of Data Science
About our Company
We are a seed-stage, clean energy startup in stealth mode backed by some of the most prominent venture investors in the industry. We’re an engineering-first company that obsesses over building cutting-edge, industry-leading products in a cross-functional and collaborative manner. We’re composed of deeply technical and experienced experts with decades of experience in both the technology and energy fields. Our mission is to accelerate our collective path to climate, electricity and societal equilibriums, and our ambitions and plans are large.
Our team is proud of our deeply collaborative culture, honest and direct but respectful communication, empathy and care for each other, and our balanced and flexible work environment. We’re looking for a few equally collaborative and talented folks to join our founding team during what is bound to be our most formative stage as a high growth company.
About the Job
At Equilibrium, we are building a company where data drives all our decision-making, and automated workflows infused with ML and AI throughout will be the engine of our success. We are looking for a Head of Data Science who shares our vision that an energy company with deep domain expertise can be built from the ground-up on data, ML and AI, and the automated workflows to autonomously act upon our data-driven insights. This person will be one of our technical visionaries plus a servant leader who can supercharge our delivery while infusing ML/AI at the core of our company foundation.
In the near-term, you will work with software engineers, data engineers, infrastructure engineers, ML engineers, product managers and product analysts to execute our ML- and AI-infused product development plan en route to earning our first company revenues and subsequent venture financing.
In the medium-term, you will nurture our data science function by cultivating a culture of experimentation and delivery, ensuring best-in-class use of ML and AI techniques, communicating ML requirements to partner engineering functions to influence their development roadmaps, setting programmatic and functional goals across multi-year horizons, helping to identify and recruit an exceptional group of data scientists with deep energy industry expertise, training new team members, and representing the data science function on the company’s executive leadership team.
- Build, nurture and grow our data science function into an industry-leading department that drives outsized growth for the company.
- Lead our most complex data science projects with hands-on analysis and modeling, drawing from the full breadth of techniques available in the industry to choose the right tool and right level of complexity appropriate for the need.
- Initiate and lead cross-functional engagements across the organization to identify, prioritize, frame, and structure complex and ambiguous challenges where advanced data science techniques, models and workflows can have the biggest impact.
- With the support of ML engineering and software engineering, structure our approach to delivering full ML / AI pipelines via requirements specification, data gathering, exploratory data analysis, model technique researching, model development, model training and testing, and model evaluation. Upon successful model development, support model deployment for operational use, model performance evaluation, and model operations support. Develop all facets of process and train team to execute process with efficiency and productivity.
- Ensure deep expertise of data structures, pipelines, and metrics throughout team, advocating for improvements where needed to improve product development.
- Partner with Product and Engineering to proactively define engineering and product landscape, roadmap, and differentiated capabilities.
- Work across the following areas:
- Exploratory Analysis: define what to build next to deliver business value; develop deep expertise into product/domain ecosystems, user behaviors, business workflows, and industry trends; proactively propose new levers to improve performance metrics.
- Model Development: lead specification, development, training and testing of our suite of ML/AI models, ultimately leading to delivery into production runtime workflows.
- Operations and Support: evaluate, define, and build testing and performance metrics; monitor model performance and understand root causes of performance; build and analyze performance dashboards and reports.
- Data and Features: develop and lead analysis, data, and feature automation strategy; drive step-change improvements into data / ML / AI feature stores; assemble key data sets to empower exploratory analysis, model development, training and testing.
- Product Vision: influence product and engineering roadmaps through presentation of data-driven recommendations, experimental results, and model performance to propagate best practices and drive long-term business value.
- Serve as a member of the company’s executive leadership team.
- BA/BS/Master's degree in a quantitative discipline (e.g., Operations Research, Mathematics, Computer Science, Economics, Physics, Electrical Engineering) or equivalent experience.
- Development experience in Python and databases (e.g., SQL)
- Knowledge of statistics (e.g., hypothesis testing, regressions)
- 6 years of work experience as a data scientist
- PhD degree in a quantitative discipline (e.g., Operations Research, Industrial Engineering, Mathematics, Computer Science, Economics, Physics, Electrical Engineering)
- 10 years of relevant work experience, including expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods.
- Advanced proficiency in Python and databases (e.g., SQL).
- Experience developing and releasing ML/AI models that support operational users (e.g., models that run and produce new inferences every hour of the day).
- Applied experience building ML and DL models in the electricity and energy domain (e.g., wholesale market price forecasting)
- Familiarity with optimization techniques (e.g., stochastic optimization, robust optimization, etc.)
- Applied experience designing and building statistical forecasting models on time series data, including characterizing probabilistic forecasting uncertainties.
- Applied experience designing and building reinforcement learning models and pipelines.
- Proactive communicator who can translate product design specs into organized code.
- Experience communicating the results of analyses with product, engineering, and leadership teams to influence product and engineering strategy.
- Demonstrated proactivity and self-direction. Willingness to teach as well as learn.
- Excellent team collaboration skills and collaboration-first mentality.
- Passion for clean energy and saving the environment a plus!
What we offer
- Opportunity to own a significant piece of the company via meaningful equity grant
- Competitive salary and comprehensive medical, dental, and vision benefits
- Opportunity to shape the company’s vision as part of the executive team
- Flexible work schedule and unlimited vacation
- Ability to work remotely from anywhere in the United States
- Deeply collaborative culture with a supportive, tight knit and fun team
- Growth opportunities to learn from other senior engineers with a diverse set of skills and experiences across energy and tech
- Extremely promising company prospects, with top tier investors and leadership team in place
Get in touch
Interested? Reach out to us at firstname.lastname@example.org. We can’t wait to tell you more about what we’re cooking up. All roles, titles and compensation packages will be tailored to the applicant, so reach out if any of the above looks interesting.