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Remote Geology Data Science Jobs in Michigan (NOW HIRING)

Senior Staff Data Engineer

Portage, MI · On-site +1

$153K - $255K/yr

Remote Join a team focused on building scalable, enterprise-grade data platforms that support ... Bachelor's degree in Computer Science, Data Analytics, Mathematics, Statistics, Data Science, or a ...

You will partner with Data Engineering, Data Science, Architecture, Infrastructure, Security, and ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

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Remote Geology Data Science information

What is a remote geology data scientist?

A Remote Geology Data Scientist is a professional who analyzes geological data using advanced data science techniques, often working from a remote location. They apply statistical models, machine learning, and programming skills to extract insights from datasets related to earth sciences, such as mineral exploration, seismic activity, or environmental monitoring. Their work supports decision-making in industries like oil and gas, mining, and environmental consulting. Remote roles leverage digital tools and communication platforms to collaborate with teams and stakeholders from anywhere in the world.

What are the key skills and qualifications needed to thrive as a remote geology data scientist, and why are they important?

To thrive as a Remote Geology Data Scientist, you need a solid background in geology, strong analytical skills, and proficiency in data science, typically supported by a degree in geosciences or a related field. Familiarity with programming languages (such as Python or R), GIS software (like ArcGIS or QGIS), and experience with data visualization and machine learning tools are commonly required. Excellent problem-solving abilities, attention to detail, and strong communication skills help convey complex geological insights to diverse stakeholders. These skills are crucial for analyzing large geoscientific datasets remotely, driving data-driven decision-making, and contributing valuable insights to geological projects.

What are some typical challenges faced by remote geology data scientists, and how can they be addressed?

Remote geology data scientists often encounter challenges related to collaborating with field teams, accessing large geospatial datasets, and ensuring data quality from a distance. Effective communication tools and regular virtual meetings help bridge the gap between remote and on-site teams. Utilizing cloud-based platforms for data storage and processing can facilitate access to large datasets, while standardized data collection protocols ensure consistency and accuracy. Building strong relationships with field personnel and staying proactive about potential data issues are key strategies for success in this role.

What are the most commonly searched types of Geology Data Science jobs in Michigan?

The most popular types of Geology Data Science jobs in Michigan are:

What are popular job titles related to Remote Geology Data Science jobs in Michigan?

For Remote Geology Data Science jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Geology Data Science jobs in Michigan look for?

The top searched job categories for Remote Geology Data Science jobs in Michigan are:

AI Training Specialist - Life Sciences

micro1 AI

Warren, MI • Remote

$90 - $120/hr

Part-time

This job post has expired today. Applications are no longer accepted.


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.