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Remote Chemical Engineering Data Science Jobs in Florida

Azure Cloud Data Engineer

Weston, FL ยท Remote

$108K - $130K/yr

AZURE DATA ENGINEER (REMOTE) ARC Group has an immediate opportunity for an aspiring Azure / Cloud ... Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics * 6+ years of ...

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Strong proficiency in data science programming languages and big data technologies, including ...

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Strong proficiency in data science programming languages and big data technologies, including ...

The individual will work closely with scientists, field teams, operations personnel, engineers, and ... soil science, remote sensing, or precision agriculture applications is highly desirable.

Data Lake Engineer

Doral, FL ยท On-site +1

$99K - $225K/yr

Master's degree in Computer Science, Information Technology, Systems Engineering, Data Science ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

Showing results 41-60

Remote Chemical Engineering Data Science information

What is a remote chemical engineering data scientist?

A Remote Chemical Engineering Data Scientist is a professional who applies data science techniques, such as machine learning and statistical analysis, to chemical engineering problems while working outside a traditional office setting. They analyze data from chemical processes, develop predictive models, and help optimize production, often collaborating with teams virtually. This role requires a strong foundation in chemical engineering principles, programming skills, and experience with data analytics tools. Working remotely offers flexibility but also demands excellent communication and self-management skills.

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

To excel as a Remote Chemical Engineering Data Scientist, you need a strong background in chemical engineering principles, data analysis, and statistical modeling, often supported by a degree in engineering or data science. Proficiency in programming languages like Python or R, experience with machine learning frameworks, and familiarity with process simulation tools are typically required. Exceptional problem-solving skills, communication, and the ability to collaborate virtually make candidates stand out in this remote environment. These capabilities are vital for transforming complex chemical process data into actionable insights and driving innovation from a distance.

How do remote chemical engineering data scientists typically collaborate with cross-functional teams?

Remote chemical engineering data scientists often work closely with R&D, process engineering, and IT teams to analyze complex datasets and develop data-driven solutions. Collaboration is facilitated through virtual meetings, shared digital platforms, and clear documentation. Regular communication and project management tools help coordinate tasks, track progress, and ensure that insights are effectively integrated into engineering projects. Building strong relationships remotely can be a challenge, but proactive communication and participation in team discussions are key to successful collaboration.

What is the difference between Remote Chemical Engineering Data Science vs Remote Chemical Engineering?

AspectRemote Chemical Engineering Data ScienceRemote Chemical Engineering
Required CredentialsBachelor's or higher in Chemical Engineering, Data Science, or related fields; knowledge of programming and data analysisBachelor's or higher in Chemical Engineering; engineering licensure may be preferred
Work EnvironmentPrimarily remote, involving data analysis, modeling, and software toolsRemote or on-site, focusing on process design, safety, and plant operations
Employer & Industry UsageTech companies, consulting firms, or R&D departments integrating data scienceManufacturing, oil & gas, pharmaceuticals, and chemical plants

Remote Chemical Engineering Data Science combines chemical engineering principles with data analysis skills, often working remotely on modeling and data-driven decision-making. In contrast, Remote Chemical Engineering focuses on process design and plant operations, which may involve on-site work. Both roles require a chemical engineering background but differ in technical focus and work environment.

What are the most commonly searched types of Chemical Engineering Data Science jobs in Florida?

The most popular types of Chemical Engineering Data Science jobs in Florida are:

What are popular job titles related to Remote Chemical Engineering Data Science jobs in Florida?

For Remote Chemical Engineering Data Science jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Remote Chemical Engineering Data Science jobs in Florida look for?

The top searched job categories for Remote Chemical Engineering Data Science jobs in Florida are:

What cities in Florida are hiring for Remote Chemical Engineering Data Science jobs?

Cities in Florida with the most Remote Chemical Engineering Data Science job openings:

Senior Computer Vision Engineer ID72408

AgileEngine

Tallahassee, FL โ€ข On-site, Remote

$99K - $136K/yr

Full-time

Posted 14 days ago


Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE
We are looking for a Senior Computer Vision Engineer to own applied model development across computer vision, machine learning, and data science use cases — building and deploying solutions for object detection, image segmentation, classification, and video analysis. You will evaluate and fine-tune model architectures using PyTorch and TensorFlow, build broader ML models for forecasting and anomaly detection, and apply practical knowledge of computer vision hardware including cameras, sensors, and edge devices.

WHAT YOU WILL DO
- Own the applied model development process across computer vision, AI/ML, and broader data science use cases;
- Translate complex business problems into viable, practical, and scalable AI/ML solutions;
- Evaluate various model options, train and fine-tune selected architectures, and rigorously analyze model performance;
- Develop and deploy solutions for object detection, image segmentation, image classification, and video analysis;
- Build and maintain models for time-series forecasting, anomaly detection, regression, clustering, and general data analysis;
- Apply practical knowledge of real-world constraints—such as lighting, sensor limitations, and edge device compute power—to ensure optimal data quality and robust model performance in production.

MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 3 to 5 years of professional experience in Computer Vision, Machine Learning, Data Science, or a related field;
- Degree in Computer Science, Engineering, Data Science, Mathematics, or a related discipline (or equivalent practical experience);
- Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
- Strong, production-level proficiency in Python;
- Deep hands-on experience with PyTorch and/or TensorFlow;
- Proven track record of building and deploying models for detection, segmentation, classification, and image/video analysis;
- Solid understanding of broader ML and data science techniques (time-series modeling, forecasting, anomaly detection, regression, and clustering);
- Practical experience working with computer vision hardware, including cameras, sensors, and lighting setups;
- Familiarity with deploying models on edge devices;
- Strong understanding of how physical and real-world constraints impact data quality, model training, and inference;
- Upper-intermediate English level.

PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.