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Remote Data Extraction Jobs in Missouri (NOW HIRING)

Design and implement advanced analytical strategies and algorithms to extract, analyze, and ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

Design and implement advanced analytical strategies and algorithms to extract, analyze, and ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

... data extraction from various sources. * Develop API-based integration solutions to improve data ... Ability to use and contribute code to repositories, i.e., local, remote, and shared (e.g., Github ...

Geospatial Data Content Manager Mid

Arnold, MO · On-site +1

$108K - $113K/yr

Ability to use and contribute code to repositories, i.e., local, remote, and shared (e.g., Github ... Proficiency in ETL (Extract, Transform, and Load) * Demonstrated experience with JavaScript

Geospatial Data Content Manager Mid

Saint Louis, MO · On-site +1

$119K - $124K/yr

Ability to use and contribute code to repositories, i.e., local, remote, and shared (e.g., Github ... Proficiency in ETL (Extract, Transform, and Load) * Demonstrated experience with JavaScript

Data Engineer-US

Columbia, MO · On-site +1

$109K - $130K/yr

Columbia, MO (Hybrid - 1 week in office, 1 week remote) Experience: 4+ years Schedule: Full-time, ... Implement ETL/ELT processes and support data modeling and data warehousing initiatives * Work with ...

Team members who choose virtual / remote work should have an adequate space to serve as their home ... Extract, clean, and manipulate structured and unstructured data from multiple sources * Perform ...

Team members who choose virtual / remote work should have an adequate space to serve as their home ... Extract, clean, and manipulate structured and unstructured data from multiple sources * Perform ...

Team members who choose virtual / remote work should have an adequate space to serve as their home ... Extract, clean, and manipulate structured and unstructured data from multiple sources * Perform ...

$81K - $111K/yr

You will design production-grade ETL/ELT pipelines, analytical models, and cloud data workflows ... Fully remote, full-time opportunity with the flexibility to work from anywhere. * Initial ...

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Remote Data Extraction information

What is remote data extraction?

Remote data extraction is the process of retrieving and collecting data from various sources—such as websites, databases, or documents—without being physically present at the source location. This is typically achieved using specialized software, scripts, or tools that can access and gather data over the internet or through remote connections. Professionals in this field often automate data collection tasks to save time and improve accuracy, especially when dealing with large volumes of information. Remote data extraction is commonly used for business intelligence, market research, competitive analysis, and data migration projects.

What are the key skills and qualifications needed to thrive as a remote data extraction specialist?

To thrive as a Remote Data Extraction Specialist, you need proficiency in data analysis, attention to detail, and experience with data extraction and transformation techniques, often supported by a degree in computer science, information systems, or a related field. Familiarity with tools such as SQL, Python, web scraping frameworks (like BeautifulSoup or Scrapy), and data management platforms is typically required. Strong problem-solving skills, self-motivation, and effective communication are valuable soft skills for excelling in a remote environment. These abilities ensure accurate data collection, efficient workflow, and reliable delivery of insights for business or research needs.

What are some common challenges faced in a remote data extraction role and how can they be addressed?

One common challenge in remote data extraction is ensuring data accuracy while working independently, especially when dealing with large and diverse datasets. Discrepancies can arise from inconsistent data formats or sources, so developing strong attention to detail and utilizing reliable extraction tools is critical. Another challenge is communication, as collaborating with data analysts or project managers remotely requires proactive updates and clear documentation. To address these issues, it's helpful to establish regular check-ins with your team, use standardized data templates, and stay organized with project management software.

What is the difference between Remote Data Extraction vs Remote Data Entry?

AspectRemote Data ExtractionRemote Data Entry
Primary FocusExtracting data from various sources like websites, PDFs, or imagesInputting data into databases or spreadsheets
Skills RequiredWeb scraping, data analysis, attention to detailTyping speed, accuracy, basic computer skills
Tools UsedWeb scraping software, OCR tools, data management platformsExcel, Google Sheets, data entry software
Work EnvironmentMostly independent, often project-basedConsistent, repetitive tasks

Remote Data Extraction involves retrieving data from various sources, requiring technical skills like web scraping and data analysis. Remote Data Entry focuses on inputting data accurately into systems, emphasizing speed and precision. Both roles are remote-friendly but differ in technical complexity and daily tasks.

What are the most commonly searched types of Data Extraction jobs in Missouri?

The most popular types of Data Extraction jobs in Missouri are:

What cities in Missouri are hiring for Remote Data Extraction jobs?

Cities in Missouri with the most Remote Data Extraction job openings:

Infographic showing various Remote Data Extraction job openings in Missouri as of August 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 100% Remote job distribution.

Data Scientist

Chesterfield, MO • On-site, Remote

Bunge North America
Software Development • 10K+ employees

Full-time

Medical, Retirement, PTO

Re-posted just now


Bunge rating

7.2

Company rating: 7.2 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

199th of 445 rated food and drinks producers


Job description

City : Chesterfield State : Missouri (US-MO) Country : United States (US) Requisition Number : 47239 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 will be an integral part of the Bunge Economic Analysis team, leveraging advanced statistical modeling, econometrics, and machine learning to analyze vast internal and external datasets. This role is crucial for developing sophisticated predictive models that inform our understanding and forecasting of global commodity market dynamics, including crop production, pricing trends, and customer behavior, thereby advancing our economic research functions worldwide.What You'll Be Doing: Collaborate effectively within cross-functional teams, including economists, market analysts, data engineers, and business leaders, to translate complex business challenges into solvable data science problems. Translate complex business problems into data-driven analytics and machine learning tasks, then design, develop, and swiftly deploy high-performance, resilient predictive models using a range of machine learning, statistical, and econometric techniques. Design and implement advanced analytical strategies and algorithms to extract, analyze, and leverage diverse data sources. Critically assess the effectiveness, accuracy, and suitability of various data inputs for global economic models. Rigorously monitor, evaluate, and refine the performance of deployed machine learning solutions to ensure sustained accuracy and measurable business impact. Clearly and effectively communicate complex analytical findings, model insights, and strategic recommendations to diverse audiences, including senior leadership, traders, and business units, supporting informed decision-making and global risk management.Skill/Experience Requirements: Minimum MS degree in Economics, Agricultural Economics, Statistics, Computer Science, Quantitative Finance, Business Analytics, or a closely related quantitative field. Minimum 2-year of professional experience in a Data Scientist or similar quantitative role, preferably within an economic analysis, commodity trading, financial services, or agribusiness environment. Expert proficiency in Python (e.g., pandas, NumPy, scikit-learn, statsmodels, TensorFlow) for data manipulation, statistical analysis, machine learning, and data visualization. Strong SQL skills for data extraction, manipulation, and analysis from relational and non-relational databases. Solid understanding of statistical inference, econometric modeling (e.g., time series analysis, causal inference), and machine learning algorithms (e.g., regression, classification, clustering, tree-based models). Demonstrated ability to frame complex problems, design analytical solutions, and extract meaningful insights from large datasets. Excellent communication and presentation skills with the ability to explain complex concepts or methods in a precise and clear manner. Detail-oriented, proactive, self-motivated, build work relationships, and able to work both independently and collaboratively in a fast-paced, dynamic global environment.Preferred Experience/Skills: 5+ years of industry work experience in Data Science fields. Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep learning for statistical modeling. Experience with big data technologies and cloud-based data platforms and products (e.g., Google Cloud Platform, AWS). Familiarity with MLOps practices for deploying, monitoring, and maintaining machine learning models in production. Specific knowledge of agricultural commodity markets (e.g., grains, oilseeds, biofuels), agronomics, etc.Bunge 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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