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Machine Learning Remote Internship Jobs in Missouri

$58.50 - $75.25/hr

Experience supporting analytics, machine learning, or AI workloads that depend on well-modeled, trusted data. * Background in retail, e-commerce, or large-scale consumer data environments. Essential ...

Senior Data Analyst

Columbia, MO · Remote

$81K - $103K/yr

Denver, CO Job Type Remote Build the Future with Us -- EquipmentShare is Hiring a Senior Data ... Experience with machine learning algorithmsKnowledge of Equipment Sales and Equipment Rental ...

Data Platform Software Engineer

Kansas City, MO · On-site +1

$111K - $134K/yr

Kansas City, MO (Remote Eligible) Company Overview : SS&C is a global leader in investment and ... and machine learning, while providing out-of-the-box deep insights. This role blends data ...

Collaborate closely with Product, Analytics, Machine Learning, Finance, and Compliance teams in an ... Remote Work - You can work from everywhere! * Home Office Bonus - A one-time allowance to help you ...

Senior Data Analyst

Columbia, MO · Remote

$81K - $103K/yr

This position is fully remote. Primary Responsibilities * Apply operations research methodologies ... Experience with machine learning algorithmsKnowledge of Equipment Sales and Equipment Rental ...

Senior Data Analyst

Columbia, MO · Remote

$81K - $103K/yr

This position is fully remote. Primary Responsibilities * Apply operations research methodologies ... Experience with machine learning algorithmsKnowledge of Equipment Sales and Equipment Rental ...

This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...

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Machine Learning Remote Internship information

What types of projects can I expect to work on during a Machine Learning Remote Internship?

During a remote machine learning internship, you can expect to contribute to projects such as data preprocessing, model development, and performance evaluation. Interns often work on real-world datasets, applying techniques like regression, classification, clustering, or deep learning, depending on the organization's focus. Collaboration with data scientists, engineers, and other interns is common, typically via virtual meetings and shared code repositories. These projects provide hands-on experience and often culminate in presenting your findings to the team, offering valuable exposure to industry-standard workflows and tools.

What is a Machine Learning Remote Internship?

A Machine Learning Remote Internship is a temporary, structured work experience where interns contribute to machine learning projects from a remote location, such as their home. Interns typically work with teams on tasks like data preprocessing, building models, and evaluating results, while gaining practical knowledge and mentoring. These internships are ideal for students or recent graduates looking to develop their skills in machine learning, programming, and data science without the need to relocate. They often involve working with Python, popular ML libraries, and real-world datasets. Communication and collaboration are maintained through online tools and regular meetings.

What are the key skills and qualifications needed to thrive as a Machine Learning Remote Intern, and why are they important?

To thrive as a Machine Learning Remote Intern, you need a solid background in programming (especially Python), mathematics/statistics, and a foundational understanding of machine learning concepts, often gained through coursework or relevant projects. Familiarity with machine learning libraries (like TensorFlow, PyTorch, and scikit-learn), version control systems (such as Git), and cloud platforms is typically expected. Strong problem-solving abilities, self-motivation, and effective remote communication set top interns apart. These skills and qualities enable efficient collaboration, successful project delivery, and continuous learning in a dynamic, distributed work environment.

What is the difference between Machine Learning Remote Internship vs Data Science Intern?

AspectMachine Learning Remote InternshipData Science Intern
Required CredentialsBasic programming, math, and machine learning knowledgeStatistics, programming, and data analysis skills
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis and modeling tasks
Industry UsageTech, AI, startups, research labsTech, finance, healthcare, consulting
Search & Comparison IntentUnderstanding internship roles in MLExploring data science internship opportunities

Machine Learning Remote Internships focus on developing models and algorithms, often requiring knowledge of programming and math. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. While both roles are remote and industry-relevant, ML internships emphasize algorithm development, whereas data science roles focus on data analysis and visualization.

What cities in Missouri are hiring for Machine Learning Remote Internship jobs? Cities in Missouri with the most Machine Learning Remote Internship job openings:
Data Scientist Geospatial Analytics

Data Scientist Geospatial Analytics

Bunge North America

Chesterfield, MO • On-site, Remote

Full-time

Medical, Retirement, PTO

Posted 14 days ago


Bunge rating

7.1

Company rating: 7.1 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

190th of 391 rated food and drinks producers


Job description

City : Chesterfield State : Missouri (US-MO) Country : United States (US) Requisition Number : 46371 A Day In The Life:Leveraging our inherent market intelligence is a critical component to Bunge?s success, particularly in the dynamic agricultural markets. This the reason why Bunge has one of the large economic analysis teams in the industry. Our analysis team is comprised of over 50 analysts world wide who gather, analyze, supply and demand and other pertinent information. The global analysts work closely with global traders to help market develop market theses that drive the company?s trading and risk decisions. The team covers global grains, oilseeds, biofuels, ocean freight and livestock.The Data Scientist, Geospatial Analytics will be a core contributor to Bunge?s Global Economic Analysis team, applying data science, satellite imagery, advanced statistical modeling, and emerging generative AI techniques to generate valuable insights across global agricultural markets. This role will lead the development of scalable, satellite-based analytics that support global crop forecasting, supply chain intelligence, and commodity market analysis. The position focuses on integrating public Earth observation data with proprietary datasets and transforming them into actionable signals that enhance our understanding of crop conditions, acreage, yield potential, and global supply-demand dynamics. What You'll Be Doing: Design, build and scale satellite-based analytics pipelines for real-time crop monitoring at globe scale; Analyze and integrate multi source datasets, including satellite imagery (Sentinel 1/2, Landsat, MODIS), weather and soil data, agricultural statistics, field level observations, and proprietary datasets Develop geospatial indicators such as NDVI anomalies, crop classifications, and yield signals to support trading and commercial decisions Leverage cloud infrastructure (e.g., Google Cloud Platform, AWS) for large scale geospatial data processing Utilize platforms and tools including Google Earth Engine, BigQuery, and Python based analytics pipelines Apply AI and machine learning techniques to imagery and time series data (e.g., classification, segmentation, feature extraction, and temporal modeling) Collaborate with economists, market analysts, data engineers, and business leaders to integrate geospatial insights into market views and fundamental analysis Monitor, evaluate, and continuously refine deployed models and analytics to ensure sustained accuracy and measurable business impact Clearly communicate complex analytical findings, model insights, and strategic recommendations to diverse audiences, including senior leadership and traders, to support informed decision making and global risk managementSkills/Experience Requirements: Master?s degree or higher in Remote Sensing, Statistics, Computer Science, or a closely related quantitative field Minimum of 5 years of professional experience in remote sensing, geospatial analytics, or agricultural data science Advanced proficiency in Python (e.g., pandas, NumPy, scikit learn, statsmodels, TensorFlow, GeoPandas, rasterio) Strong SQL skills for data extraction, manipulation, and analysis across large datasets Solid understanding of geospatial data systems, projections, and large scale processing workflows Demonstrated ability to translate complex data and models into practical agricultural, commercial, or market insights Excellent communication and presentation skills, with the ability to explain complex analytical concepts clearly and concisely Highly detail oriented, proactive, and self motivated, with the ability to work both independently and collaboratively in a fast paced, global environmentPreferred Skills/Experience: Background in agriculture, crop modeling, or commodity research Experience working with radar data and vegetation indices Exposure to yield modeling, acreage estimation, or crop classification workflows Knowledge of agricultural commodity markets (e.g., grains, oilseeds, biofuels) and agronomic conceptsBunge offers a variety of benefits including health and wellness plans, retirement contribution and paid vacation/holidays.At Bunge (NYSE: BG), our purpose is to connect farmers to consumers to deliver essential food, feed and fuel to the world. As a premier agribusiness solutions provider, our team of 34,000 dedicated employees partner with farmers across the globe to move agricultural commodities from where they?re grown to where they?re needed in faster, smarter, and more efficient ways. We are a world leader in grain origination, storage, distribution, oilseed processing and refining, offering a broad portfolio of plant-based oils, fats, and proteins. We work alongside our customers at both ends of the value chain to deliver quality products and develop tailored, innovative solutions that address evolving consumer needs. With 200+ years of experience and presence in over 50 countries, we are committed to strengthening global food security, advancing sustainability, and helping communities prosper where we operate. Bunge has its registered office in Geneva, Switzerland and its corporate headquarters in St. Louis, Missouri. Learn more at Bunge.com.Every day our people exemplify these values, which represent Bunge at its core: We Are One Team Collaborative, Respectful, Inclusive We Lead The Way Agile, Empowered, Innovative We Do What?s Right Safety, Sustainability, With IntegrityIf this sounds like you, join us! We value and invest in people who believe in our purpose and are excited to live it every day people who are #ProudtoBeBunge

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