[Hiring] Machine Learning Scientist @GoodPower

Role Description

GoodPower seeks a Machine Learning Scientist to expand what our teams and software can accomplish through applied research, predictive modeling, and intelligent automation. You will identify where Artificial Intelligence/ Machine Learning (AI/ML) can improve decisions, unlock new offerings, and reduce the time and cost of delivering our work. Your mandate spans clean energy planning, public participation integrity, media and narrative intelligence, and organizational effectiveness.

You will own the scientific development of ML capabilities from problem definition and experimentation through validation and deployment with engineering partners. Success means demonstrably better decisions, more useful products, and greater team capacity, supported by rigorous evidence and clear communication of uncertainty. The Machine Learning Scientist will report to the Chief Innovation Officer.

Key Responsibilities

• Applied Research and Model Development
  • Translate user needs and strategic challenges into tractable ML problems.
  • Establish baselines, define success criteria, and prioritize experiments by potential impact, data readiness, and feasibility.
  • Develop models for classification, entity resolution, anomaly detection, forecasting, ranking, and risk assessment using text, geospatial, energy, market, media, and organizational data.
  • Combine sources to reveal patterns that improve decisions.
  • Select and test methods suited to the problem, from statistical models and classical ML to deep learning, graph methods, and LLMs.
  • Use predictive models, optimization, and scenario analysis to evaluate options and allocate resources.
• Data Quality and Scientific Evaluation
  • Build representative datasets, labeling strategies, and evaluation benchmarks.
  • Prevent leakage and test performance across time, geography, groups, and unfamiliar contexts using validation appropriate to the intended use.
  • Quantify uncertainty, calibration, and the consequences of false positives and false negatives.
  • Make research reproducible through versioned data, code, and experiments.
• LLM and Agentic Systems
  • Build retrieval and synthesis systems that turn heterogeneous documents and data into verifiable answers and actionable intelligence.
  • Develop agents that use tools, models, and internal services to complete useful workflows.
  • Evaluate hosted and open-weight models, prompting, fine-tuning, and distillation against quality, privacy, latency, and cost requirements.
  • Establish evaluation and monitoring for LLM and agent systems, including factual accuracy, robustness, task completion, and operating cost.
• Production Integration and Shared Capabilities
  • Shape reusable data representations, feature pipelines, retrieval services, and model interfaces.
  • Partner with software and ML engineers to move validated prototypes into reliable products.
• Technical Direction and Measurable Impact
  • Identify high-value opportunities beyond existing platform roadmaps.
  • Work with product, research, communications, and program teams to understand user decisions and constraints.
  • Define and track outcomes such as decision quality, predictive performance, user adoption, analyst time saved, and cost per workflow.

Qualifications

• PhD in machine learning, computer science, statistics, or a related quantitative field, with 3-5 years of applied ML experience.
• Evidence of turning ambiguous problems into rigorous experiments and useful AI/ML capabilities.
• Hands-on experience with NLP and LLM applications.
• Strong Python skills and experience with tools such as PyTorch/TensorFlow, scikit-learn, and pandas.
• Sound statistical judgment and the ability to work with heterogeneous, incomplete, or noisy data.
• Ability to own technical work, prioritize under uncertainty, and communicate findings to technical and nontechnical colleagues.

Preferred

• Experience with energy, climate, grid, infrastructure siting, permitting, regulatory, or public participation data.
• Publications, open-source contributions, or deployed projects demonstrating methodological depth, originality, and practical impact.

Benefits

• Annual salary range: $160,000-190,000, commensurate with experience.
• Medical, dental, and vision insurance with employee and dependent premiums paid at 95-100% by GoodPower.
• 2-4 weeks of paid vacation annually, depending on seniority.
• 13 paid holidays and 2 floating holidays.
• 2 weeks of US office closure.
• 10 days of paid sick leave annually.
• 403(b) with 3% employer contribution/match.
• Charitable giving: 1:1 match for charitable contributions ($250 per year), plus 2 paid days off for volunteering.
• Education reimbursement up to $1,500 per year.
• Healthcare Flexible Spending Account (FSA) and Health Savings options.
• Stipend of $200/month (for cell phone, wellness expenses, etc.).
• 8 weeks of paid sabbatical after 5 years of employment.
• 8 weeks of paid parental leave.