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Data Science Jobs in Washington, MO (NOW HIRING)

Data Scientist

Chesterfield, MO ยท On-site

$110 - $150/hr

Data Scientist Date: Aug 10, 2026 Location: Chesterfield, MO -Missouri, US, 63017 City ... Minimum MS degree in Economics, Agricultural Economics, Statistics, Computer Science, Quantitative ...

The Data Scientist will be an integral part of the Bunge Economic Analysis team, leveraging ... Minimum MS degree in Economics, Agricultural Economics, Statistics, Computer Science, Quantitative ...

The role combines data science, statistical modeling, geospatial analysis, and business expertise to optimize the branch and ATM network and support strategic decision-making. Responsible for ...

Computer Vision and Data Analysis Co-Op In this role, you will analyze and summarize data generated ... This position is based on a hybrid work model at the Bayer Crop Science facility in Chesterfield ...

New

Data Engineer II

O Fallon, MO ยท On-site

$107K - $128K/yr

You will collaborate with engineers, data scientists, risk analytics, and product partners to translate business needs into effective data products and pipelines. This is an opportunity for an ...

Data Engineer II

O Fallon, MO ยท Hybrid

$107K - $128K/yr

You will collaborate with engineers, data scientists, risk analytics, and product partners to translate business needs into effective data products and pipelines. This is an opportunity for an ...

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Data Science information

See Washington, MO salary details

$33.2K

$108.5K

$173.8K

How much do data science jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data science in Washington, MO is $108,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,100.00 and $120,300.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What job categories do people searching Data Science jobs in Washington, MO look for?

The top searched job categories for Data Science jobs in Washington, MO are:

What cities near Washington, MO are hiring for Data Science jobs?

Cities near Washington, MO with the most Data Science job openings:

Infographic showing various Data Science job openings in Washington, MO as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $108,543 per year, or $52.2 per hour.

Data Scientist

Bunge Iberica SA

Chesterfield, MO โ€ข On-site

$110 - $150/hr

Other

Medical, Retirement, PTO

Posted 23 days ago


Key responsibilities

  • Collaborate with cross-functional teams to translate business challenges into data science problems and develop predictive models.

  • Design, develop, and deploy analytical strategies and machine learning models to analyze diverse data sources and support economic forecasting.

  • Communicate analytical findings and model insights to stakeholders to inform decision-making and risk management.


Job description

Data Scientist

Date: Aug 10, 2026

Location: Chesterfield, MO -Missouri, US, 63017

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 Bungeโ€™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 worldโ€‘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 companyโ€™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 theyโ€™re grown to where theyโ€™re neededโ€”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 โ€“ Collaborative, Respectful, Inclusive
  • We Lead The Way โ€“ Agile, Empowered, Innovative
  • We Do Whatโ€™s Right โ€“ Safety, Sustainability, With Integrity

If 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 โ€“ people who are #ProudtoBeBunge


Nearest Major Market: St Louis
Job Segment: Agronomy, Agricultural, Database, Scientific, Machinist, Agriculture, Engineering, Technology, Manufacturing

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