1

Data Preprocessing Jobs in Chicago, IL (NOW HIRING)

Services of the platform include data preprocessing, AI model fine-tuning, inference oversight and MLOps for AI solutions in production. For traditional enterprises that have an aspiration to ...

AI/ML Computational Science Engineer

Chicago, IL ยท On-site

$26.39 - $77.88/hr

Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production * Implement and maintain efficient data storage and retrieval ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Services of the platform include data preprocessing, AI model fine-tuning, inference oversight and MLOps for AI solutions in production. For traditional enterprises that have an aspiration to ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Services of the platform include data preprocessing, AI model fine-tuning, inference oversight and MLOps for AI solutions in production. For traditional enterprises that have an aspiration to ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ...

Showing results 21-40

Data Preprocessing information

See Chicago, IL salary details

$47.4K

$170K

$250.8K

How much do data preprocessing jobs pay per year?

As of Sep 13, 2026, the average yearly pay for data preprocessing in Chicago, IL is $169,993.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,500.00 and $175,100.00 per year, depending on experience, location, and employer.

What is data preprocessing?

Data preprocessing is the process of cleaning, transforming, and organizing raw data into a usable format for analysis or machine learning. It involves steps such as handling missing values, removing duplicates, normalizing or scaling data, and encoding categorical variables. Proper data preprocessing helps improve the quality and performance of predictive models by ensuring the data is accurate, consistent, and suitable for analysis.

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

To thrive as a Data Preprocessing Specialist, you need a strong background in statistics, data cleaning, and data transformation, often supported by a degree in computer science, data science, or a related field. Proficiency with tools such as Python (pandas, NumPy), SQL, and data visualization platforms is typically essential, along with familiarity with data management systems. Attention to detail, problem-solving abilities, and effective communication are standout soft skills in this position. These skills are crucial for ensuring high-quality, reliable datasets that underpin accurate data analysis and machine learning outcomes.

What are some common challenges faced in a data preprocessing role, and how can they be effectively managed?

Professionals in Data Preprocessing often encounter challenges such as handling incomplete or inconsistent data, managing large datasets, and ensuring data quality before analysis. Addressing these issues typically involves using specialized tools to automate data cleaning, establishing clear data validation rules, and collaborating closely with data engineers and analysts. Staying updated with best practices and leveraging scripting languages like Python or R can also streamline the preprocessing workflow, making it easier to deliver reliable and accurate datasets for downstream analysis.

What is the difference between Data Preprocessing vs Data Analysis?

AspectData PreprocessingData Analysis
Primary FocusCleaning, transforming, and preparing raw data for analysisInterpreting data to extract insights and support decision-making
Skills RequiredData cleaning, scripting, understanding of data formatsStatistical analysis, data visualization, critical thinking
Work EnvironmentData engineering teams, data science projectsBusiness intelligence, research, data science teams
Tools UsedPython, R, SQL, ETL toolsExcel, Tableau, R, Python, statistical software

While data preprocessing involves preparing raw data for analysis by cleaning and transforming it, data analysis focuses on interpreting the prepared data to uncover trends and insights. Both roles are essential in the data pipeline but serve different purposes in the data lifecycle.

What are popular job titles related to Data Preprocessing jobs in Chicago, IL?

For Data Preprocessing jobs in Chicago, IL, the most frequently searched job titles are:

What cities near Chicago, IL are hiring for Data Preprocessing jobs?

Cities near Chicago, IL with the most Data Preprocessing job openings:

Infographic showing various Data Preprocessing job openings in Chicago, IL as of June 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% In-person job distribution, with an average salary of $169,993 per year, or $81.7 per hour.

Forward Deployed Engineer

Chicago, IL โ€ข On-site

Full-time

Posted 12 days ago


Job description

At CloudFactory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world. By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale.

More than just a workplace, we're a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following.

Our Culture

At CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are:

  • Mission-Driven: We focus on creating economic and social impact.
  • People-Centric: We care deeply about our team's growth, well-being, and sense of belonging.
  • Innovative: We embrace change and find better ways to do things together.
  • Globally Connected: We foster collaboration between diverse cultures and perspectives.

If you're passionate about innovation, collaboration, and making a real impact, we'd love to have you on board!

Role Summary:

Cloudfactory is an AI enablement company where our software platform enables trusted AI at scale. Services of the platform include data preprocessing, AI model fine-tuning, inference oversight and MLOps for AI solutions in production. For traditional enterprises that have an aspiration to leverage AI to disrupt their industries but lack the skills or capabilities needed to design, prove, develop and deploy AI solutions we offer Forward deployed Engineering services that can advise, design, prove, develop, scale and operate AI solutions for them.

You will work directly with strategic clients to design and implement scalable technical integrations, define production-ready workflows, and ensure AI systems transition from experimentation to reliable deployment.

This is a hands-on engineering role with strong product and client-facing responsibilities.

Location & Travel:

  • Preferred location:
    • Dallas, TX
    • Boston, MA
    • New York, NY
    • Seattle, WA
    • Chicago, IL
  • Relocation assistance available for qualified candidates
  • Frequent travel to client sites may be required (depending on client needs)

Responsibilities:

AI Deployment Architecture:

  • Design and implement integrations between client systems and CloudFactory's platform
  • Architect scalable agentic AI & human-in-the-loop workflows
  • Define data ingestion, transformation, and feedback loops
  • Evaluate system bottlenecks (latency, quality, throughput)

Product Readiness & Scale:

  • Translate proof-of-concept AI systems into scalable production workflows
  • Identify operational risks before deployment
  • Partner with Delivery teams to ensure execution feasibility
  • Improve reliability and reduce manual intervention

Hands-on Engineering:

  • Build APIs, connectors, automation scripts, and data pipelines
  • Debug integration issues in client environments
  • Contribute to internal platform enhancements

Field Product Intelligence:

  • Surface recurring patterns from client deployments
  • Distinguish between custom solutions and reusable features
  • Influence roadmap priorities with evidence from the field

Technical Leadership:

  • Lead technical discovery sessions
  • Support pre-sales validation
  • Act as trusted advisor to enterprise engineering teams