Machine Learning Scientist - Staff/Sr Staff

December 11, 2023

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Equilibrium Energy

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Description

• Influence product and engineering roadmaps through presentation of research insights, experimental results, and model performance metrics, in order to evolve organizational direction. • Initiate and lead cross-functional engagements to surface, prioritize, formulate, and structure complex and ambiguous challenges where advanced novel deep learning research can have outsized company impact. • Formulate and apply novel machine learning solutions to the energy domain. • Tackle complex deep learning & machine learning problems by researching published academic literature, surveying industry techniques & intuition, and executing hands-on experimental testing & modeling. • Drive the design, specification, development, and production deployment of our suite of novel deep learning & machine learning solutions. • Lead short to medium term research projects that advance the state-of-the-art in deep learning as applied to energy asset management and financial trading. • Define and evaluate a suite of success metrics across our portfolio of candidate and deployed machine learning models in order to understand operational characteristics, diagnose sources of under-performance, and identify opportunities for further research & improvement.

Requirements

• Passion for clean energy and fighting climate change • An advanced degree in computer science, data science, machine learning, artificial intelligence, operations research, engineering, or related quantitative discipline • 4+ years experience in data science, research science, machine learning, or similar role, applying and adapting deep learning, graph neural networks, or reinforcement learning techniques to time series regression & forecasting problems • 2+ years experience in the electricity & energy domain (e.g. electricity price forecasting, congestion prediction etc) • 3+ years experience with python and the supporting computational science tool suite (e.g. numpy, scipy, pandas, scikit-learn, tensorflow, etc.) • Experience developing, releasing, and tracking performance of ML models in production • Experience communicating mathematical concepts, analytical results, and data-driven insights to both technical and non-technical audiences • A collaboration-first mentality, with a willingness to teach as well as learn from others • Nice to have additional skills: o Experience designing and building novel statistical models on time series data, including characterizing probabilistic outcome uncertainty o Experience with dimensionality reduction, component decomposition, or embedding space analysis & visualization techniques (e.g. UMAP, T-SNE, Autoencoder) o Experience with model explainability methods (e.g. SHAP) o Experience with database technologies and sql o Experience with probability, hypothesis testing, and uncertainty quantification o Experience with optimization techniques (e.g. stochastic optimization, robust optimization) o Experience with data visualization and dashboarding technologies (e.g. plot.ly Dash, Streamlit) o Experience leading and mentoring a team of scientists o Demonstrated track record of academic paper or social media publication

Benefits

• Competitive base salary and a comprehensive medical, dental, vision, and 401k package • Opportunity to own a significant piece of the company via a meaningful equity grant • Unlimited vacation and flexible work schedule • Ability to work remotely