Research Engineer - Energy Markets

Description

******* Required Application Step*********

East Daley Analytics uses Predictive Index as part of its hiring process. Candidates must complete both assessments to be considered for this role: Click to take assessments 

East Daley Analytics provides proprietary intelligence on North American energy infrastructure, commodity markets, and public energy companies. Our Equity Research team combines fundamental market analysis with asset-level financial modeling to determine how changes in production, flows, prices, contracts, and infrastructure affect company earnings and investment outcomes.

Our Mission: At East Daley, we move the market. We connect physical energy-market signals to financial performance so investors and industry leaders can understand what is changing, which companies are exposed, and where our outlook differs from consensus. We are building the next generation of energy equity research through proprietary data, rigorous analysis, and technology.

We are looking for: A highly resourceful Research Engineer to become a force multiplier for our Equity Research team. You will work directly with analysts to understand how they research companies and markets, identify where their workflows can be improved, and build tools that increase the speed, quality, and depth of their work.

You will use Python, SQL, AI, automation, and proprietary energy data to turn recurring analytical problems into scalable solutions. You will also explore the data independently, challenge assumptions, build market models, and develop differentiated views on energy markets and company performance.

The ideal candidate is a builder and problem-solver who can enter an ambiguous situation, learn the business context, find the right data, ship a practical solution, and explain why the result matters.

Why This Role Is Different

• Work directly with Equity Research analysts covering public energy companies and serving institutional investors and energy-industry clients.
• Build tools that immediately influence research quality, forecast accuracy, and client decisions.
• Work with proprietary asset, production, flow, contract, infrastructure, and financial data.
• Own projects end-to-end, from problem definition and raw data through deployment, market interpretation, and client-facing output.
• Exercise meaningful autonomy to identify high-value problems, propose solutions, and drive them to implementation.
• Help define how AI changes the way equity research and energy-market analyses are performed.
• Develop a rare combination of technical, financial, and energy-market expertise.

Role Responsibilities

• Work directly with Equity Research analysts to understand their workflows, identify recurring bottlenecks, and determine      where technology can improve speed, quality, and analytical depth. 
• Own solutions from problem definition through development, testing, deployment, adoption, and iteration. 
• Build tools and automations that reduce manual data work and allow analysts to spend more time interpreting markets and      companies. 
• Develop reliable data pipelines, scrapers, transformations, internal applications, and analytical models using Python and SQL. 
• Connect asset, production, flow, contract, infrastructure, ownership, company, and financial data across East Daley’s systems. 
• Build workflows that translate physical market activity into revenue, EBITDA, capital expenditures, company forecasts,      and investment implications. 
• Transform recurring Excel-based processes into structured, reusable, and supportable systems. 
• Reconcile inconsistent datasets, identifiers, ownership structures, reporting periods, and company disclosures. 
• Develop models and analyses that identify emerging trends, unusual signals, forecast risks, and differentiated market views. 
• Translate technical outputs into clear market, financial, and investment implications. 
• Apply appropriate testing, quality controls, monitoring, version control, and documentation. 
• Communicate progress, risks, design decisions, and tradeoffs clearly across analytical, engineering, product, and visualization teams.

How We Expect You to Use AI

AI should be an active development and analytical partner in how you work. We expect this person to go beyond basic prompting and use AI to accelerate research, coding, debugging, testing, documentation, data reconciliation, prototyping, and analytical discovery.

Strong candidates will know how to turn AI into a repeatable workflow, critically evaluate its output, and build controls that make AI-assisted work accurate and reproducible. During the interview process, candidates should be prepared to demonstrate a specific example of how they used AI to materially improve a technical or analytical workflow.

Compensation

• Salary range: $75,000 - $85,000 plus bonus opportunities
• Full-time, exempt position based in Greenwood Village, Colorado
• Reports to Equity Research Team Lead

Benefits

• Medical, Dental, and Vision coverage with Company contributions
• 401(k) with a 3% Company contribution
• Flexible Spending and Health Savings Account options with Company Contribution
• Employee Assistance and Wellness Programs
• Life, Accidental Death, and Disability coverage
• Direct access to experienced analysts, engineers, and energy-market professionals
• Meaningful ownership of analytical tools and client-facing products
• Exposure to proprietary energy infrastructure, financial, regulatory, and market data
• Opportunity for rapid development across software, AI, financial analysis, equity research, and energy markets
• Employees are welcome to bring their well-behaved dogs to the office.  

Requirements

Minimum Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, Finance, Geology, Energy, or a related field
• Practical experience using Python and SQL to solve real analytical or operational problems
• Demonstrated use of generative AI to improve a technical, analytical, or software-development workflow
• Understanding of relational databases, data transformations, joins, and structured data
• Demonstrated ability to turn an ambiguous problem into a working technical solution
• Experience turning raw data into a useful tool, model, application, or analytical product
• Strong critical-thinking skills and a willingness to investigate why results do not reconcile
• Evidence of resourcefulness, ownership, and independent learning
• Ability to communicate technical findings clearly to non-technical audiences
• Strong written and verbal communication skills
• Proficiency with Microsoft Excel and PowerPoint

Preferred Qualifications

• Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, Finance, Geology, Energy,      or a related field
• Experience with pandas, NumPy, Git, APIs, web scraping, orchestration, or automated data pipelines
• Experience building internal tools, lightweight applications, dashboards, or analytical products
• Experience with AI coding assistants, agentic development tools, model APIs, retrieval systems, structured outputs, or      automated evaluations
• Experience building repeatable AI-enabled workflows rather than relying on one-time prompts
• Experience with Tableau, Power BI, Plotly, or similar visualization tools
• Experience with Excel automation, Power Query, or VBA
• Familiarity with financial statements, company modeling, investment analysis, or equity research
• Familiarity with natural gas, crude oil, NGLs, midstream infrastructure, or broader energy markets
• Familiarity with SEC, FERC, EIA, pipeline, production, or regulatory data
• Experience working with large, messy, disconnected, or imperfect datasets
• Familiarity with machine-learning methods and applied model evaluation

What Success Looks Like

A successful Research Engineer will:

• Become deeply familiar with how the Equity Research team analyzes companies and markets. 
• Build tools and automations that analysts adopt and rely on in their daily work. 
• Measurably reduce manual work, research cycle time, and avoidable errors. 
• Improve the reliability, scalability, and transparency of the team’s analytical workflows. 
• Surface differentiated market or company insights that would not have been identified through existing processes. 
• Connect physical energy-market data to company financial performance and investment implications. 
• Own technical solutions beyond the initial prototype, including testing, documentation, maintenance, and iteration. 
• Use AI to improve development speed and analytical depth without sacrificing judgment or reliability. 
• Identify high-value problems independently rather than waiting for detailed instructions. 
• Become a trusted technical and analytical partner to every member of the Equity Research team

Please note that this job description is not designed to cover every activity, duty, or responsibility required of the employee. Duties and responsibilities may change at any time with or without notice.

East Daley Analytics is an Equal Employment Opportunity employer and welcomes all qualified applicants. Applicants will receive fair and impartial consideration without regard to race, sex, color, religion, national origin, age, disability, veteran status, genetic data, or any other legally protected status.