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Mathematical Optimization Remote Jobs in Florida

Dlapiper

Data Scientist

Miami, FL · On-site +1

Mines and analyzes data to drive optimization and improvement of product development, marketing ... Bachelor's degree in computer science, data science, statistics, applied mathematics or related ...

Block

Remote (US / Canada) Duration: Fall/Winter 2026 co-op - 8 months, flexible start September 2026 ... Strong foundations in modern machine learning, including deep learning, optimization ...

Block

Remote (US / Canada) Duration: Fall/Winter 2026 co-op - 8 months, flexible start September 2026 ... Strong foundations in modern machine learning, including deep learning, optimization ...

Block

Remote (US / Canada) Duration: Fall/Winter 2026 co-op - 8 months, flexible start September 2026 ... Strong foundations in modern machine learning, including deep learning, optimization ...

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Mathematical Optimization Remote information

What is a mathematical optimization remote job?

A Mathematical Optimization Remote job involves using mathematical techniques and algorithms to solve optimization problems, such as maximizing efficiency or minimizing costs, while working from a remote location. Professionals in this field apply optimization theory, modeling, and computational methods to real-world problems in industries like logistics, finance, engineering, and data science. Remote roles allow for flexibility, enabling collaboration with teams and clients online while leveraging specialized software and programming languages such as Python, MATLAB, or R.

What are the key skills and qualifications needed to thrive as a mathematical optimization specialist working remotely?

To thrive as a Mathematical Optimization Specialist in a remote setting, you need a strong background in mathematics, operations research, or computer science, often supported by an advanced degree. Proficiency with optimization software (such as Gurobi, CPLEX, or MATLAB), programming languages like Python or R, and familiarity with cloud-based collaboration tools is typically required. Excellent problem-solving abilities, self-motivation, and clear communication skills help you stand out when collaborating with distributed teams and stakeholders. These skills and qualities are crucial for efficiently developing, implementing, and explaining optimization solutions in a remote work environment.

What are some common challenges faced by professionals in remote mathematical optimization roles, and how can they be addressed?

Remote mathematical optimization professionals often encounter challenges such as limited real-time collaboration with team members, managing complex problem-solving tasks independently, and ensuring effective communication of technical findings to non-technical stakeholders. To address these challenges, it's helpful to establish regular virtual meetings, use collaborative tools for sharing code and results, and develop clear documentation. Additionally, proactively seeking feedback and staying engaged with the broader team can help maintain alignment and foster innovation.

What is the difference between Mathematical Optimization Remote vs Data Analyst Remote?

AspectMathematical Optimization RemoteData Analyst Remote
Required CredentialsDegree in Mathematics, Operations Research, or related field; proficiency in optimization softwareDegree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentRemote, often collaborative with teams on complex modeling projectsRemote, focused on data collection, visualization, and reporting
Industry UsageFinance, logistics, supply chain, tech companiesMarketing, finance, healthcare, tech companies
Common Search/ComparisonYesNo

Mathematical Optimization Remote specialists focus on developing algorithms to optimize processes and decision-making, often requiring advanced mathematical skills. Data Analysts Remote interpret data to provide insights, using statistical tools. While both roles are remote and involve data, they differ in technical focus and industry applications.

What are the most commonly searched types of Mathematical Optimization jobs in Florida?

The most popular types of Mathematical Optimization jobs in Florida are:

What are popular job titles related to Mathematical Optimization Remote jobs in Florida?

For Mathematical Optimization Remote jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Mathematical Optimization Remote jobs in Florida look for?

The top searched job categories for Mathematical Optimization Remote jobs in Florida are:

What cities in Florida are hiring for Mathematical Optimization Remote jobs?

Cities in Florida with the most Mathematical Optimization Remote job openings:

Mathematical Optimization Remote jobs near you

Senior Computer Vision Engineer ID72408

Orlando, FL • On-site, Remote

AgileEngine
Software Development • 201 - 500 employees
Learn more about AgileEngineexternal

$97K - $133K/yr

Full-time

Posted 22 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.