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Data Preprocessing Jobs in Solon, OH (NOW HIRING)

SCATR Corp.

Artificial Intelligence Engineer

Cleveland, OH

$111K - $133K/yr

Knowledge of data preprocessing techniques and tools. * Familiarity with cloud platforms and services (e.g., AWS, Google Cloud, Azure) for deploying AI models * Networking fundamentals (e.g. common ...

Varsity Tutors

Machine Learning Tutor

Akron, OH · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Cleveland, OH · Remote

$18 - $40/hr

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

All JobsData Preprocessing JobsData Preprocessing Jobs in Solon, OH

Data Preprocessing information

See Solon, OH salary details

$42.8K

$153.4K

$226.4K

How much do data preprocessing jobs pay per year?

As of Jun 29, 2026, the average yearly pay for data preprocessing in Solon, OH is $153,404.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,100.00 and $158,000.00 per year, depending on experience, location, and employer.

What is the highest paying job in data?

In data-related fields, roles such as Data Science Director, Machine Learning Engineer, and Chief Data Officer tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in data analysis, programming, and leadership, along with extensive experience and relevant certifications.

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.

Is 40 too late for data science?

Data preprocessing is a key step in data science, and individuals can enter the field at any age. Many data scientists start later in life, and acquiring skills in programming, statistics, and tools like Python or R can facilitate entry regardless of age.

What do you do in data preprocessing?

Data preprocessing involves cleaning and transforming raw data to prepare it for analysis or modeling. This includes tasks such as handling missing values, removing duplicates, normalizing data, and encoding categorical variables, often using tools like Python or R. It is a crucial step to ensure data quality and improve model performance.

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.

Will AI replace data analysts?

AI is transforming data analysis by automating routine tasks such as data cleaning and basic reporting, but data analysts are still essential for interpreting complex insights, making strategic decisions, and applying domain knowledge. The role is evolving to include skills in machine learning tools and programming languages like Python or R, but human expertise remains critical for nuanced analysis and contextual understanding.

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 cities near Solon, OH are hiring for Data Preprocessing jobs? Cities near Solon, OH with the most Data Preprocessing job openings:
Data Preprocessing jobs near you
Infographic showing various Data Preprocessing job openings in Solon, OH 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 $153,404 per year, or $73.8 per hour.

Artificial Intelligence Engineer

SCATR Corp.

Cleveland, OH

$111K - $133K/yr

Other

Posted 11 days ago

Job description

Company Overview:

SCATR – THE DATA CAMOUFLAGE COMPANY™

Born from warfighter requirements and inspired by the animal kingdom’s natural defense mechanisms, we developed patented, quantum-resistant Data Camouflage™ technology for data in motion—safeguarding enterprises and the individuals who depend on them.

The STUN™ security platform empowers organizations to proactively secure data in motion across untrusted networks, providing data obfuscation, resiliency, and quantum-proof security. Our patented, quantum-resistant Data Camouflage™ technology allows enterprises to secure their data in motion across the world’s most hostile environments, addressing a critical gap in Zero Trust security architectures that often focus on protecting data at rest (ZTN) and data in use (ZTNA).

We integrate with global providers like Amazon Web Services, Microsoft Azure, Google Cloud and Equinix to enhance our placement and access, offering true edge to enterprise solutions.

SCATR is Zero Trust Transit™ security for data in motion.

Job Overview:

We are looking to add an experienced Artificial Intelligence (AI) Engineer to our dynamic team and contribute to the development of a robust AI-enabled solution. As an AI Engineer, you will be responsible for designing, implementing, testing and maintaining high-performance AI and machine learning models and algorithms, ensuring its compatibility and optimization across diverse software deployments. This role involves working closely with software engineers and other stakeholders to build intelligent systems that enhance our business operations and product offerings.  The ideal candidate will have a strong background in AI, machine learning and data science, with experience in deploying AI solutions in a production environment.

Responsibilities:

  • Design, develop and maintain AI and ML Models and algorithms using the latest technologies and best practices. 
  • Collaborate with cross-functional teams, including product management and UI/UX design, to gather requirements and ensure the successful implementation of AI-driven features.
  • Optimize and fine-tune models for performance, accuracy and scalability.
  • Deploy AI models, processes, and systems for knowledge sharing and reproducibility.
  • Translate business requirements into technical designs and code implementations, ensuring the delivery of high-quality software solutions.
  • Write efficient and maintainable code that meets the project's functional and performance requirements.
  • Conduct thorough testing and debugging of applications to ensure software quality and reliability.
  • Work closely with Quality Assurance teams to identify and fix software defects and inconsistencies.
  • Stay updated with the latest industry trends, technologies and best practices for AI-enabled software development.
  • Participate in code reviews, provide constructive feedback and continuously seek opportunities for codebase improvement.
  • Collaborate with the DevOps team to automate build, deployment and testing processes.
  • Assist in providing timely resolution of customer-reported issues.

Why SCATR?

  • Innovative Technology: Work with cutting-edge technologies that are transforming data security.
  • Collaboration & Growth: Join a dynamic team where your contributions directly impact global organizations' ability to secure their data in motion.
  • Competitive Benefits: We offer a comprehensive benefits package, flexible working hours and the opportunity to work on impactful projects.

Preferred Requirements:

  • Bachelor’s or Master’s degree in computer science, Data Science, Artificial Intelligence, or a related field
  • Proven experience as an AI engineer, machine learning engineer, or similar role
  • Strong understanding of machine learning algorithms, neural networks, and deep learning
  • Proficiency in programming languages such as Python, R, C++, or Java
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, Caffe, Keras, or similar
  • Knowledge of data preprocessing techniques and tools.
  • Familiarity with cloud platforms and services (e.g., AWS, Google Cloud, Azure) for deploying AI models
  • Networking fundamentals (e.g. common protocols, network structures, etc.)
  • Experience with source control tools (e.g., Git) and project management systems.
  • Familiarity with Agile software development practices and the ability to work in a collaborative team environment.
  • Excellent problem-solving and analytical skills, with a keen eye for detail.
  • Strong communication and teamwork skills, with the ability to effectively collaborate with both technical and non-technical stakeholders.
  • Ability to work in a fast-paced, dynamic environment and quickly adapt to changing priorities and project needs.

Apply