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Data Preprocessing Jobs in Texas (NOW HIRING)

Perform data preprocessing, feature engineering, and model evaluation. * Utilize Scikit-learn for model development and experimentation. * Develop and maintain applications and services using Java ...

Sr. Machine Learning Engineer

Austin, TX · On-site

$113K - $136K/yr

Perform feature engineering, data preprocessing, and exploratory data analysis. * Evaluate and optimize model performance using appropriate metrics and validation techniques. * Implement and fine ...

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

Work with large datasets and perform data preprocessing, feature engineering, and model evaluation. Collaborate with data engineers, software developers, and business stakeholders to understand ...

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Expertise in AI/ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and the end-to-end AI development lifecycle, including data preprocessing, model training, and deployment.

... data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions. · Lead cross-functional collaborations to integrate Generative AI models ...

Principal AI Software Engineer

Irving, TX · On-site

$125K - $168K/yr

... perform data preprocessing and cleaning. • Strong analytical and problem-solving skills. • Excellent communication and collaboration abilities. • Bachelor's or Master's degree in Computer ...

... data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions. • Lead cross-functional collaborations to integrate Generative AI models ...

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Data Preprocessing information

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 in Texas are hiring for Data Preprocessing jobs? Cities in Texas with the most Data Preprocessing job openings:
Data Analyst with Security Clearance

Data Analyst with Security Clearance

PlanIT Group LLC

Grand Prairie, TX • On-site

Contractor

Posted 6 days ago


Key responsibilities

  • Design, build, and maintain data pipelines and infrastructure to support analytics and AI initiatives.

  • Develop, train, and deploy machine learning and AI models for predictive and prescriptive use cases.

  • Analyze large, complex datasets to extract insights and communicate findings to stakeholders.


Job description

We are seeking a skilled Data & AI Specialist to design, develop, and deploy data-driven solutions that leverage artificial intelligence and machine learning. This role bridges data engineering, analytics, and AI model development to deliver actionable insights and scalable intelligent systems that support business objectives.
Design, build, and maintain data pipelines and infrastructure to support analytics and AI initiatives
Develop, train, and deploy machine learning and AI models for predictive and prescriptive use cases
Analyze large, complex datasets to extract insights and communicate findings to stakeholders
Collaborate with cross-functional teams to identify opportunities for AI-driven improvements
Implement data preprocessing, feature engineering, and model evaluation techniques
Monitor model performance and retrain models as needed to ensure accuracy and relevance
Ensure data quality, integrity, and governance across systems
Stay up to date with emerging trends in AI, machine learning, and data technologies Basic Qualifications:
1) Data Analysis Experience
2) Quality Analysis Experience
3) Software and Programming Skills Experience
4) Trend Analysis Experience Looking for talent who are able to develop AI bots to deploy and make efficiency gains in our teams ability to identify and find trends quickly in a fast paced environment.