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About This Role
What We Can Achieve Together:
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The Sustainable Agriculture Economist will join the Science and Standards team to support regenerative agriculture initiatives by conducting economic and market assessments that help advance practical, scalable conservation outcomes in working lands and agrifood systems. In this role, you will contribute to project teams that assess market dynamics for agricultural commodities, identify opportunities that could enable more resilient and diversified production systems, and synthesize findings into clear decision\-support materials.
They will work in a collaborative, matrixed environment alongside conservation practitioners, scientists, other economists and financial specialists, corporate engagement staff, and external partners. Your analyses will help teams understand market conditions, supply chain considerations, risk factors, and the economic feasibility of regenerative farming approaches, turning complex information into actionable insights that can inform strategy development and partner engagement. You will also support the Science and Standards team as it develops recommendations for companies on how to better align their sustainability and business strategies, working closely with NatureVest’s Financial Advisory team to provide analyses and guidance on how enhancing the resilience of their sourcing regions and supply chains can strengthen core business strategies, reduce exposure to operational and reputational risks, and unlock long term economic returns.
More specifically, the Sustainable Agriculture Economist will support ongoing efforts to understand market dynamics that influence the diversification of agricultural landscapes. This will include assessing current market conditions, risks, and opportunities related to minor crops that could be scaled across the Upper Midwest to enhance socio\-economic and environmental outcomes. In addition, this role will lead economic analyses evaluating the impacts of regenerative and conservation practices at both the farm and landscape levels, generating practical insights to inform effective strategies that support agricultural producers.
This is a temporary, remote position for 12 months. Candidates need to be based in the United States.
Note: Applicants are encouraged to apply early, as this position may close once a sufficient pool of qualified candidates has been identified.
Responsibilities \& Scope
- Conduct market, farm, and landscape level economic analyses (i.e., Return on Investment, profits and losses, statistical regressions and projections on key variables), to assess opportunities, risks, and enabling conditions that influence regenerative and diversified agricultural systems.
- Evaluate supply chain dynamics, policy landscapes, and non\-cost factors relevant to the adoption and scaling of target cropping systems.
- Synthesize data from industry sources, prior analyses, and stakeholder input into concise insights that support strategy development and decision\-making (if primary data is needed, this will be collected in collaboration with other team members).
- Prepare high\-quality written reports and presentations that communicate key findings and recommendations to internal and external audiences.
- Coordinate with cross\-functional teams and partners to gather information, validate assumptions, and support efficient project execution.
- Collaborate with external consultants and contribute to the development and preparation of follow‑on proposals or RFPs for additional analyses and strategic work.
We’re Looking for You:
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Are you looking for a career to help people and nature? Guided by science, TNC creates innovative, on\-the\-ground solutions to our world’s toughest challenges so that people and nature can thrive together. We are seeking a curious, analytically strong, and mission\-driven early\-career economist/analyst who can turn data and research into practical insights that support regenerative agriculture outcomes. If you enjoy solving problems, can communicate effectively with both technical and non\-technical audiences, and are comfortable collaborating across disciplines and teams, this opportunity is ideal for you!
What You’ll Bring:
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- Master’s degree in Agricultural Economics, Economics, Agricultural Business, or a related field.
- 1 year of relevant experience (internships, fellowships, research assistant roles, or full\-time experience) supporting market research, or economic analysis, consulting, or applied research.
- Familiarity with agrifood supply chains and topics such as regenerative agriculture, crop diversification, sustainability markets, corporate sustainability, and conservation finance.
- Demonstrated experience preparing well\-structured reports and building presentation materials for professional audiences.
- Strong quantitative and qualitative research skills, including the ability to locate, clean, interpret, and synthesize secondary datasets and industry sources and to document assumptions, limitations, and citations with rigor.
- Strong writing and communication skills—able to translate technical insights into clear takeaways.
- Ability to coordinate across teams and stakeholders in a decentralized environment.
- Fluency in English (additional languages a plus).
Desired Qualifications:
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- Experience with market landscape analysis (e.g., market sizing, segmentation, competitor/actor mapping, trend analysis).
- Exposure to policy analysis (e.g., incentives, programs, standards, regulatory context) and ability to summarize implications for market adoption.
- Comfort working with imperfect data and triangulating insights from multiple sources.
- High attention to detail, strong project management habits, and excellent organizational skills.
- Proficiency with analytical tools such as Excel and at least one of R, Python, Stata, or similar (or a strong willingness to learn quickly).
Note: Applicants are encouraged to apply early, as this position may close once a sufficient pool of qualified candidates has been identified.
Salary Information:
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The starting pay range for a candidate selected for this position is generally within the range of $65,000\- $85,000 . This range only applies to candidates whose country of employment is the USA. Where a successful candidate’s actual pay will fall within this range will be based on a variety of factors, including, for example, the candidate's location, qualifications, specific skills, and experience. Please note countries outside the USA would have a different pay range in the local currency based on the local labor market, and not tied to USA pay or ranges. Your geographic location will be confirmed during the recruitment.
### Who We Are :
The Nature Conservancy’s mission is to protect the lands and waters upon which all life depends. As a science\-based organization, we create innovative, on\-the\-ground solutions to our world’s toughest challenges so that we can create a world in which people and nature thrive. We’re rooted in our mission and guided by our values, which include respect for all people, communities, and cultures. Whether it’s career development, flexible schedules, or a rewarding mission, there’s many reasons to love life inside TNC. Want a better insight to TNC? Check out our TNC Talent playlist on YouTube to hear stories from staff or visit Glassdoor .
One goal is to cultivate an inclusive work environment so that all our colleagues around the globe feel a sense of belonging and that their unique contributions to our mission are valued. In addition to the requirements in our job postings, we recognize that people come with talent and experiences outside of a job and consider each applicant’s unique experience. Please apply – we’d love to hear from you. To quote a popular saying at TNC, “you’ll join for the mission, and stay for the people.”
### What We Bring:
Since 1951, TNC has been doing work you can believe in. Through grassroots action, we have grown from a small non\-profit into one of the most effective and wide\-reaching environmental organizations in the world. Thanks to more than 1 million members, over 400 scientists, and the dedicated efforts of our diverse staff and partners, we impact conservation around the world!
TNC offers a competitive, comprehensive benefits package including health care benefits, flexible spending accounts, a 401(k) plan with an 8% employer match, parental leave, accrued paid time off, life insurance, disability coverage, employee assistance program, other life and work well\-being benefits.
We’re proud to offer a flexible work environment that supports of the health and well\-being of the people we employ.
Our recruiting process includes a rolling interview process to ensure we engage applicants in a timely manner. This means we may review applications in the order in which they are received. Once a strong candidate pool is identified, the role will be unposted. The timeline may vary depending on the expressed interest in the role, so we highly encourage candidates to apply as soon as possible.
Employees must submit their application by logging into Workday and applying via the Jobs Hub.
The Nature Conservancy is an Equal Opportunity Employer. Our commitment to equal employment opportunity includes the recognition that our conservation mission is best advanced by the leadership and contributions of people of all backgrounds, beliefs, and culture. Recruiting and mentoring staff to create an inclusive organization is a priority, and we encourage applicants from all cultures, races, colors, religions, sexes, national or regional origins, ages, disability status, sexual orientation, gender identity, military, protected veteran status or other status protected by law.
The successful applicant must meet the requirements of The Nature Conservancy's background screening process.
Do you have military experience? Visit our U.S. Military Skills Translator to match your military experience with our current job openings!
TNC is committed to offering accommodations for qualified individuals with disabilities and disabled veterans in our job application process. If you need assistance or an accommodation due to a disability, please send a note to applyhelp@tnc.org with Request for Accommodation in the subject line.
Salary Context
This $65K-$85K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At The Nature Conservancy, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($75K) sits 55% below the category median. Disclosed range: $65K to $85K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
The Nature Conservancy AI Hiring
The Nature Conservancy has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $85K - $85K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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