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ComboCurve is a cloud-based software platform for asset development, reservoir management, and forecasting in the energy sector. This role leads the creation of basin and equity research products that combine well-level technical analysis with corporate financial modeling and valuation.
The position owns two interconnected research streams:
**Basin & Play Research**: Produce top-well rankings, subplay studies, completion-design trend analysis, and operator benchmarking. Audience is E&P executives evaluating asset performance and competitive positioning.
**Equity Research**: Cover public E&P companies using bottom-up well-level forecasts rather than relying on management guidance. Develop NAV, inventory depth, corporate cash flow, leverage, hedge position, and valuation views. Audience is institutional investors and executives concerned with investor perception.
The core differentiator is that all conclusions are built from well-level data upward, with transparent methodology at every layer. When your NAV disagrees with a company's disclosure, you can point to specific wells and explain why.
**Key Responsibilities:**
- Design defensible study populations: build well datasets from commercial and public sources, define screening criteria (vintage floors, lateral length minimums, completion intensity, production history), and publish the screening waterfall showing what each criterion removed.
- Identify and account for data quality issues: null proppant, perforated vs. drilled lateral length, re-fracs booked as single events, operator misassignments post-acquisition.
- Run decline curve analysis at scale (hundreds to thousands of wells): set Arps parameters, b factors, Di, terminal decline; build type curves and P10/P50/P90 bands; normalize EUR to common lateral length.
- Execute full-cycle economics: vintage-tiered and lateral-length-based CAPEX, fixed and variable OPEX, flat and strip pricing, NPV, IRR, payout with price sensitivities.
- Build corporate models from well-level forecasts: production by asset, capital program, cash flow, leverage, hedge book, NAV, and inventory depth across price decks.
- Reconcile against public disclosure: read 10-Ks, reserve reports, investor decks, and transcripts; be specific about where and why your numbers differ.
- Perform spatial analysis in QGIS or ArcGIS: subplay delineation, EUR interpolation surfaces, permit and lateral overlays, acreage and inventory footprints by operator.
- Publish at two depths: write full 20–50 page studies with detailed exhibits and auditable methodology appendices, then compress to two-page executive summaries without losing defensibility.
- Maintain publishing cadence of 1–2 studies per month plus responsive pieces when markets move.
- Present at industry conferences (URTeC, SPE ATCE, NAPE, energy investor conferences) and support executive and investor conversations.
- Provide product feedback: your workflow is the customer workflow; flag platform bottlenecks with specifics.
**Requirements:**
- Technical foundation in subsurface: BS in petroleum engineering, geological engineering, or geoscience, or equivalent hands-on experience.
- 3+ years in energy research, technical evaluation, or energy equity research and investing.
- Production forecasting fluency: understand b factors above 1.0, when to override decline curve assumptions, and how to QC forecasts at scale.
- Economics fluency: NPV, IRR, payout, price decks, CAPEX tiering, differentials; ability to identify what conclusions are sensitive to.
- Corporate modeling experience: can build from well-level forecasts to cash flow, NAV, and valuation views (not just read outputs).
- Comfort with public filings and reserve reports; healthy skepticism about their limitations.
- Hands-on experience with commercial well databases (S&P Global, Enverus, TGS, or similar) including their failure modes.
- Long-form technical writing: hold a thesis across extended documents without data-dumping; build auditable methodology appendices.
- Compression skills: distill detailed studies to two pages while preserving defensibility.
- Publishable work samples: research, investor materials, papers, or internal studies that influenced decisions (team bylines acceptable; clarify your contributions).
- Willingness to be the named author: you will be cited, quoted, and occasionally debated publicly.
**Strongly Preferred:**
- ComboCurve experience or deep familiarity with comparable platforms (ARIES, PHDWin, Val Nav).
- Sell-side, buy-side, or data/analytics research background with an existing audience.
- QGIS or ArcGIS at production level.
- Python or SQL for data prep, QC, and batch work; BigQuery or similar a plus.
- Multi-basin exposure: Permian, Haynesville, Eagle Ford, Bakken, DJ, Appalachia, Uinta.
- Visual and design judgment or tools (Figma, Illustrator, or equivalent).
