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Remote Conservation Data Science Jobs in Montana

Senior AI Product Manager

Bozeman, MT · On-site +1

$129K - $170K/yr

You will collaborate directly with engineering, data science, and design teams to deliver high ... Reliable internet connection required during remote work periods How You'll Be Rewarded Salary ...

Senior AI Product Manager

Bozeman, MT · On-site +1

$129K - $170K/yr

You will collaborate directly with engineering, data science, and design teams to deliver high ... Reliable internet connection required during remote work periods How You'll Be Rewarded ✅ Salary ...

Data Center COE Project Manager

Bozeman, MT · Remote

$131K/yr

Remote in the US #LI-Remote This role is contributing to the Electrification Services Business Area ... A Bachelor of Science degree in Mechanical or Electrical Engineering highly preferred. Combination ...

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Remote Conservation Data Science information

What are the key skills and qualifications needed to thrive as a remote conservation data scientist?

To thrive as a Remote Conservation Data Scientist, you need expertise in data analysis, ecological modeling, and a strong background in environmental science or a related field, often supported by an advanced degree. Proficiency with programming languages like Python or R, GIS tools (such as ArcGIS or QGIS), and relevant data management systems is essential. Excellent problem-solving, communication, and collaboration skills are crucial for translating data insights into actionable conservation strategies with remote teams. These abilities enable effective data-driven decision-making and foster impactful conservation outcomes across diverse and distributed environments.

How does a remote conservation data scientist typically collaborate with field teams and stakeholders?

Remote conservation data scientists often rely on digital communication tools—such as video calls, shared databases, and project management platforms—to work closely with field researchers, conservation managers, and external partners. While they may not be physically present at field sites, they regularly interpret, analyze, and visualize data collected on the ground, providing actionable insights for ongoing projects. Regular virtual meetings are common for aligning on project goals, discussing data quality, and adapting analytical approaches based on field realities. This collaborative structure ensures that data-driven recommendations are both relevant and grounded in real-world conservation challenges.

What is a remote conservation data scientist?

A Remote Conservation Data Scientist is a professional who analyzes environmental data to support conservation efforts, often working from a location outside of a traditional office or onsite fieldwork setting. They use data science techniques such as statistical analysis, machine learning, and geographic information systems (GIS) to interpret data related to biodiversity, ecosystems, wildlife populations, and climate change. Their work helps inform conservation policies, resource management, and strategies to protect natural habitats. Remote work in this field relies heavily on digital collaboration tools and access to large datasets. These scientists often partner with non-profits, government agencies, or research organizations to tackle global conservation challenges.
Infographic showing various Remote Conservation Data Science job openings in Montana as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 12% Part Time, 1% Temporary, 7% Contract, and 1% Nights. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.

Digital Chemistry Specialist - Remote

micro1 AI

Billings, MT • Remote

$90 - $120/hr

Part-time

Posted 9 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.