# Biofuels/Biodiesel Technology and Product Development Managers

> Define, plan, or execute biofuels/biodiesel research programs that evaluate alternative feedstock and process technologies with near-term commercial potential.

- **SOC code:** 11-9041.01
- **Canonical URL:** https://singulariki.com/roles/role-11-9041-01
- **Also known as:** Analytical Research Program Manager, Biodiesel Division Manager, Laboratory Manager (Lab Manager), Project Development Director, Biofuels Manager, Business Development and New Technology Manager, Biodiesel Engineering Manager, Biodiesel Product Development Manager
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Design or conduct applied biodiesel or biofuels research projects on topics, such as transport, thermodynamics, mixing, filtration, distillation, fermentation, extraction, and separation.
- Analyze data from biofuels studies, such as fluid dynamics, water treatments, or solvent extraction and recovery processes.
- Prepare, or oversee the preparation of, experimental plans for biofuels research or development.
- Provide technical or scientific guidance to technical staff in the conduct of biofuels research or development.
- Propose new biofuels products, processes, technologies or applications based on findings from applied biofuels or biomass research projects.
- Conduct experiments on biomass or pretreatment technologies.
- Prepare biofuels research and development reports for senior management or technical professionals.
- Develop lab scale models of industrial scale processes, such as fermentation.
- Oversee biodiesel/biofuels prototyping or development projects.
- Develop methods to estimate the efficiency of biomass pretreatments.
- Conduct experiments to test new or alternate feedstock fermentation processes.
- Perform protein functional analysis and engineering for processing of feedstock and creation of biofuels.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- English Language _(knowledge)_
- Chemistry _(knowledge)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Problem Sensitivity _(ability)_
- Deductive Reasoning _(ability)_
- Engineering and Technology _(knowledge)_
- Written Expression _(ability)_
- Information Ordering _(ability)_
- Oral Expression _(ability)_
- Inductive Reasoning _(ability)_
- Reading Comprehension _(essential_skill)_

**Skills in demand:**
- English Language _(Common Skill)_
- Chemistry _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Writing _(Common Skill)_
- Systems Analysis _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Mathematics _(Common Skill)_
- Active Listening _(Common Skill)_

**Tools & technology:**
- Adobe Illustrator _(hot technology)_
- Epic Systems _(hot technology)_
- Linux _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft SQL Server _(hot technology)_
- Microsoft SQL Server Integration Services SSIS _(hot technology)_
- Microsoft SQL Server Reporting Services SSRS _(hot technology)_
- Microsoft Visio _(hot technology)_
- Microsoft Word _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 59th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 68th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 57th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 56th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 13th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.8% growth (About average); 14.5k annual openings; 212.5k → 220.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $167,740; 210,340 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-11-9041-01_