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Remote Data Analyst Side Jobs in Missouri (NOW HIRING)

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 ...

Senior Financial Analyst

Des Peres, MO · Remote

$84K - $105K/yr

Remote This is a remote position, with preference given to candidates located within the St. Louis ... This role is well suited for an experienced finance professional who enjoys working with data ...

$94K - $116K/yr

You will identify business questions, extract data through relational databases or cloud platforms, analyze and interpret the data and develop insights into stories to assist with business-critical ...

Remote (Must be located near Indianapolis, IN or St. Louis, MO) Department: Solutions Accounting ... Extract internal source data to perform statistical, cost, and operational financial analyses ...

Senior Financial Analyst

Saint Louis, MO · On-site +1

$79K - $110K/yr

... Remote #InternalOps How you'll make an impact in this role * Financial Analytics & Reporting: Extract internal source data to perform statistical, cost, and operational financial analyses ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Showing results 41-60

Remote Data Analyst Side information

What is a remote data analyst side?

A remote data analyst side job involves working part-time or as a freelancer to analyze data for organizations, all while working from a location outside the traditional office. Responsibilities typically include collecting, cleaning, and interpreting data to help businesses make informed decisions. This role allows professionals to leverage their analytical skills in a flexible setting, often outside of their primary job or commitments. Remote data analyst side jobs are ideal for those seeking additional income or experience without the constraints of a full-time, in-office position. Common industries hiring for these roles include marketing, finance, healthcare, and technology.

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

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in a quantitative field such as mathematics or computer science. Familiarity with data analysis tools and programming languages such as SQL, Python, R, and platforms like Tableau or Power BI is typically required. Excellent problem-solving abilities, self-motivation, and clear communication skills set top remote analysts apart. These skills are essential for extracting actionable insights from data and effectively collaborating with distributed teams to support business decisions.

What are some common challenges faced by remote data analysts, and how can they be effectively addressed?

Remote data analysts often face challenges such as limited access to immediate team collaboration, potential data security concerns, and managing time across different time zones. To overcome these, it's important to leverage communication tools like Slack or Microsoft Teams for regular check-ins, use secure VPNs and follow company data protocols, and establish clear work schedules with your team. Proactively seeking feedback and maintaining organized documentation can also help ensure smooth workflow and effective collaboration.

What is the difference between Remote Data Analyst Side vs Remote Data Analyst?

AspectRemote Data Analyst SideRemote Data Analyst
CredentialsBachelor's in Data Science, Statistics, or related field; proficiency in Excel, SQL, Python/RBachelor's or higher in Data Science, Statistics, or related; similar technical skills
Work EnvironmentPart-time, freelance, or side projects; flexible hoursFull-time or part-time; employed by companies or clients
Employer & Industry UsageFreelance platforms, startups, consulting firmsCorporations, consulting agencies, research firms

The main difference is that a Remote Data Analyst Side typically works on freelance or part-time projects, offering flexibility, while a Remote Data Analyst is usually employed full-time or part-time by organizations. Both roles require similar skills and credentials, but their work settings and commitments differ.

Data Scientist

Bunge

Chesterfield, MO • On-site, Remote

Full-time

Medical, Retirement, PTO

Posted 28 days ago


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 worldwide 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 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 - people who are #ProudtoBeBunge



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