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Data Preprocessing Jobs in Emerson, NJ (NOW HIRING)

Errgo

Junior Machine Learning Engineer

Manhattan, NY · On-site

$85 - $110/hr

Write Python code for data preprocessing, feature engineering, and model evaluation * Help build and maintain ML pipelines for training and inference * Collaborate with data engineers to access and ...

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Data Preprocessing information

See Emerson, NJ salary details

$47K

$168.8K

$249K

How much do data preprocessing jobs pay per year?

As of Aug 22, 2026, the average yearly pay for data preprocessing in Emerson, NJ is $168,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,500.00 and $173,800.00 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.

Data Preprocessing jobs near you
Infographic showing various Data Preprocessing job openings in Emerson, NJ as of June 2026, with employment types broken down into 42% Internship, and 58% Full Time. Highlights an 100% In-person job distribution, with an average salary of $168,753 per year, or $81.1 per hour.

Junior Machine Learning Engineer

Errgo

Manhattan, NY • On-site

$85 - $110/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Job description

As a Junior Machine Learning Engineer, the candidate will contribute to building and deploying ML models that power intelligent features across the platform. This role offers the opportunity to work alongside experienced ML engineers and data scientists, gaining hands-on experience with the full machine learning lifecycle—from data preparation and model training through evaluation and production deployment.The ideal candidate is passionate about machine learning, has strong programming fundamentals, and is eager to apply academic knowledge to real-world problems. This position provides mentorship, exposure to production ML systems, and the opportunity to grow technical skills in a supportive environment.The engineer will work on meaningful projects that directly impact users, learning MLOps best practices while contributing to model development and pipeline maintenance.

What you'll do
  • Assist in developing and training machine learning models using PyTorch or TensorFlow
  • Write Python code for data preprocessing, feature engineering, and model evaluation
  • Help build and maintain ML pipelines for training and inference
  • Collaborate with data engineers to access and process training data
  • Document model performance, experiments, and technical decisions
  • Learn MLOps practices and contribute to model deployment workflows
What you bring
  • 0-2 years of experience in machine learning or data science
  • Strong Python skills with experience in ML libraries (PyTorch, TensorFlow, scikit-learn)
  • Understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics)
  • Familiarity with SQL and data manipulation (pandas, numpy)
  • Exposure to cloud platforms (AWS, GCP) is a plus
  • Bachelor's or Master's degree in Computer Science, Statistics, or related field
What you get
  • Medical, dental, and vision insurance
  • 401(k)
  • Paid time off

Job details and compensation are subject to change.

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