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Remote Climate Data Scientist Jobs in Minnesota (NOW HIRING)

Director of Data Intelligence | Remote | Michigan or Minnesota Preferred Role Snapshot: * Set the ... Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ...

New

Ability to critically review and interpret scientific and clinical trial data, and oversee the ... We recognize the benefits of flexible, remote working arrangements for eligible roles and are ...

Earth Science Tutor

Minneapolis, MN ยท Remote

$18 - $40/hr

... to climate. Adapts instruction using rock and mineral samples, weather data analysis, and interactive mapping tools to support middle and high school students building scientific literacy.

Showing results 21-40

Remote Climate Data Scientist information

What is a remote climate data scientist?

A Remote Climate Data Scientist is a professional who analyzes large sets of climate-related data, often from various sources such as weather stations, satellites, and climate models, to uncover trends and provide insights about climate change. They work remotely, using advanced statistical and machine learning techniques to interpret data and make predictions that can inform policy, research, and business decisions. Their work helps drive understanding of environmental patterns, supports climate resilience planning, and contributes to scientific publications or organizational strategy. Being remote, they collaborate with teams and stakeholders virtually, utilizing digital tools to communicate and share findings.

What is the difference between Remote Climate Data Scientist vs Remote Environmental Data Analyst?

AspectRemote Climate Data ScientistRemote Environmental Data Analyst
Required CredentialsDegree in Climate Science, Data Science, or related field; proficiency in Python, R, GIS toolsDegree in Environmental Science, Data Analysis, or related; skills in statistical software and data visualization
Work EnvironmentResearch institutions, climate-focused organizations, government agenciesEnvironmental consulting firms, NGOs, government agencies
Industry UsageClimate modeling, policy analysis, sustainability projectsEnvironmental impact assessments, resource management, conservation projects

The main difference is that Remote Climate Data Scientists focus on climate-specific data modeling and analysis, often involving climate change projections, while Remote Environmental Data Analysts work on broader environmental issues like resource management and conservation. Both roles require strong data skills and often overlap in work environment and credentials, but their focus areas differ within the environmental sector.

How do remote climate data scientists typically collaborate with team members and stakeholders across different time zones?

Remote Climate Data Scientists often work with multidisciplinary teams that may be distributed globally. Effective collaboration relies on clear communication through digital channels like Slack, video meetings, and project management tools. Regularly scheduled check-ins, shared documentation, and flexible work hours help ensure everyone stays aligned despite time zone differences. Being proactive in sharing progress updates and seeking feedback is key to successful teamwork in this remote, international environment.

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

To thrive as a Remote Climate Data Scientist, you need a strong background in climate science, statistics, and data analysis, typically supported by an advanced degree in environmental science, data science, or a related field. Expertise in programming languages like Python or R, experience with climate modeling tools, and familiarity with cloud-based data platforms are commonly required. Strong problem-solving abilities, self-motivation, and clear communication are critical for collaborating remotely and translating complex data into actionable insights. These skills ensure accurate climate predictions, effective teamwork across locations, and valuable contributions to climate research and policy.
What are the most commonly searched types of Climate Data Scientist jobs in Minnesota? The most popular types of Climate Data Scientist jobs in Minnesota are:
What job categories do people searching Remote Climate Data Scientist jobs in Minnesota look for? The top searched job categories for Remote Climate Data Scientist jobs in Minnesota are:
What cities in Minnesota are hiring for Remote Climate Data Scientist jobs? Cities in Minnesota with the most Remote Climate Data Scientist job openings:

Digital Chemistry Specialist - Remote

micro1 AI

Saint Paul, MN โ€ข 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 โ€” 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.