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Remote Manufacturing Data Scientist Jobs in Colorado

Senior Machine Learning Scientist

Boulder, CO ยท On-site +1

$96K - $131K/yr

Work with large-scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis. Build and oversee reproducible workflows for data processing ...

Senior Machine Learning Scientist

Boulder, CO ยท On-site +1

$96K - $131K/yr

Work with large-scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis. Build and oversee reproducible workflows for data processing ...

Senior Wetlands Scientist

Boulder, CO ยท On-site +1

$94K - $129K/yr

We are hiring a Senior Wetland Scientist to lead that work, combining wetland science, remote ... Data integration: integrate LiDAR-derived elevation, hydrology, imagery, soils, and existing ...

Senior Wetlands Scientist

Boulder, CO ยท On-site +1

$90K - $130K/yr

We are hiring a Senior Wetland Scientist to lead that work, combining wetland science, remote ... Data integration: integrate LiDAR-derived elevation, hydrology, imagery, soils, and existing ...

Showing results 41-60

Remote Manufacturing Data Scientist information

What does a remote manufacturing data scientist do?

A Remote Manufacturing Data Scientist analyzes large sets of manufacturing data to uncover insights, optimize processes, and support decision-making, all while working offsite. They use statistical methods, machine learning, and data visualization tools to identify patterns, predict equipment failures, and recommend improvements for efficiency and quality. Collaborating with engineering and production teams, they help implement data-driven solutions without being physically present at the manufacturing facility. Their work contributes to reducing costs, improving productivity, and ensuring product quality in the manufacturing sector.

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

To thrive as a Remote Manufacturing Data Scientist, you need expertise in data analytics, statistical modeling, and a solid educational background in fields like computer science, engineering, or statistics. Familiarity with programming languages (such as Python or R), machine learning platforms, and manufacturing-specific systems like ERP or MES is typically required. Strong problem-solving skills, attention to detail, and effective remote communication are essential soft skills for collaborating with cross-functional teams. These competencies enable you to extract actionable insights from complex manufacturing data, driving process improvements and operational efficiency from a remote setting.

How does a remote manufacturing data scientist typically collaborate with onsite engineering and production teams?

As a Remote Manufacturing Data Scientist, collaboration with onsite teams is often facilitated through regular virtual meetings, shared dashboards, and collaborative project management tools. You may analyze production data, develop predictive models, and then present insights and recommendations to engineers and plant managers via video calls or detailed reports. Building strong communication skills and familiarity with digital collaboration platforms is essential for bridging the gap between remote analytics and hands-on manufacturing processes. Proactively seeking feedback and clarifying technical requirements with onsite teams ensures your data-driven solutions are both practical and impactful.

What is the difference between Remote Manufacturing Data Scientist vs Remote Manufacturing Engineer?

AspectRemote Manufacturing Data ScientistRemote Manufacturing Engineer
Required CredentialsDegree in Data Science, Statistics, or related field; proficiency in data analysis toolsDegree in Mechanical, Industrial, or Manufacturing Engineering; technical skills in manufacturing processes
Work EnvironmentPrimarily analytical, working with data sets and software tools remotelyFocus on process design, optimization, and technical implementation, often involving remote collaboration
Industry UsageUsed across manufacturing sectors for data-driven decision makingApplied in designing and improving manufacturing systems and processes

The main difference is that a Remote Manufacturing Data Scientist focuses on analyzing manufacturing data to inform decisions, while a Remote Manufacturing Engineer concentrates on designing and optimizing manufacturing processes. Both roles may work remotely and require technical expertise, but their core responsibilities differ significantly.

What are popular job titles related to Remote Manufacturing Data Scientist jobs in Colorado?

For Remote Manufacturing Data Scientist jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Remote Manufacturing Data Scientist jobs in Colorado look for?

The top searched job categories for Remote Manufacturing Data Scientist jobs in Colorado are:

What cities in Colorado are hiring for Remote Manufacturing Data Scientist jobs?

Cities in Colorado with the most Remote Manufacturing Data Scientist job openings:

Infographic showing various Remote Manufacturing Data Scientist job openings in Colorado as of June 2026, with employment types broken down into 73% Full Time, 15% Part Time, 2% Temporary, 8% Contract, and 2% Nights. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution.

Senior Machine Learning Scientist

3M HEALTHCARE

Boulder, CO โ€ข On-site, Remote

$96K - $131K/yr

Full-time

Medical, Retirement

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Company Description Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health, sustainability and beyond exponentially accelerate scientific progress in areas ranging from disease detection and treatment and nature-positive agriculture to novel applications of AI that are driving the creation of new technologies. What sets Flagship apart is our ability to advance science and technology by uniting innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet. Many of the companies Flagship has founded have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. The Role We are seeking a Senior Machine Learning Scientist, Climate and Hydrology to lead the scientific direction and machine learning development for hydrology-aware climate modeling within our broader environmental modeling platform. This role sits at the intersection of hydrology, weather and climate science, and large-scale machine learning. The Sr. Scientist will help shape how hydrologic process understanding, climate data, and modern ML methods are brought together in next-generation prediction systems, with emphasis on scientifically grounded model development and evaluation. The individual in this role will work across science, ML, engineering, and data teams to define research priorities, guide model training and benchmarking, build reproducible workflows, and translate scientific insight into scalable model development. This is a cross-functional role requiring strong technical depth, structured scientific thinking, and the ability to move between foundational research and applied execution. Key Responsibilities Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning. Help define research priorities, modeling directions, and evaluation strategies for next-generation climate and environmental prediction systems. Contribute to the development and improvement of ML-based modeling approaches informed by physical and Earth system science. Work with large-scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis. Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation. Collaborate closely with research, engineering, and data teams to translate scientific goals into scalable technical execution. Guide assessment of model performance, uncertainty, and scientific robustness across a range of environmental conditions and applications. Communicate findings through internal reviews, external collaborations, publications, and technical presentations. Help shape the broader scientific roadmap and contribute to team growth and cross-functional leadership. Professional Experience & Qualifications PhD in machine learning, computational science, Earth science, atmospheric science, hydrology, AI, computer science, or a related quantitative discipline. 5+ years of postdoctoral, industry, or applied research experience in climate ML, weather ML, hydrologic modeling, Earth system modeling, or a closely related field. Demonstrated experience with ML-accelerated weather, climate, or hydrology models, with a strong publication track record in the area. Experience working with large climate datasets, including reanalysis products, remote sensing datasets, observational datasets, and model output. Experience with the computational infrastructure required to manage, preprocess, and train on large-scale climate datasets, preferably in the AWS ecosystem. Strong programming skills in Python and experience with modern ML frameworks such as PyTorch. Background in scientific ML, spatiotemporal modeling, data assimilation, hybrid physics-ML methods, or related approaches is strongly preferred. Ability to design rigorous evaluation frameworks, performance metrics, and benchmarking approaches for environmental prediction systems. Strong technical writing and communication skills, including reports, presentations, and peer-reviewed publications. Demonstrated ability to work independently in fast-paced, ambiguous environments while collaborating effectively across disciplines. Experience leading cross-functional scientific efforts, mentoring researchers, or helping define research roadmaps is preferred. Location Cambridge, MA or Boulder, CO (some travel to Cambridge, MA based headquarters if working from Colorado). About Flagship Pioneering Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com. At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact. Equal Opportunity Employer We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Salary and Benefits The salary ranges for this role are $127,000 - $205,900 (Colorado) and $168,000 - $231,000 (Massachusetts). Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Protocos currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Protoco's good faith estimate as of the date of publication and may be modified in the future. #J-18808-Ljbffr