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Data Preprocessing Jobs in Pennsylvania (NOW HIRING)

Senior ML/MLOps Engineer

Pittsburgh, PA ยท On-site

$97K - $134K/yr

Develop robust and scalable pipelines for data preprocessing, model training, and deployment. . Strong programming skills in Python and in similar languages. . Familiarity with machine learning ...

Artificial Intelligence Engineer

Pittsburgh, PA ยท Hybrid

$111K - $133K/yr

Conducts data analysis, preprocessing, training, testing, validating and feature engineering to extract valuable insights from large datasets, improving model performance and accuracy. * Stays ...

Artificial Intelligence Engineer

Pittsburgh, PA ยท On-site

$111K - $133K/yr

Conducts data analysis, preprocessing, training, testing, validating and feature engineering to extract valuable insights from large datasets, improving model performance and accuracy. * Stays ...

ML Engineer

United, PA ยท On-site

... data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments. โ€ข Participate in continuous improvement of the ML infrastructure and processes for ...

Research Specialist

Pittsburgh, PA ยท On-site

$20 - $30.55/hr

This individual will administer research protocols, facilitate study procedures, maintain accurate and complete documentation, and ensure timely data storage, backup, and preprocessing. The position ...

Senior Robotics AI Engineer

Philadelphia, PA ยท On-site

$99K - $137K/yr

... data collection, labeling, preprocessing and validation pipelines to ensure high-quality training datasets. โ€ข Implement robust simulation and field testing workflows, along with production ...

Senior Robotics AI Engineer

Philadelphia, PA ยท On-site

$99K - $137K/yr

... data collection, labeling, preprocessing and validation pipelines to ensure high-quality training datasets. โ€ข Implement robust simulation and field testing workflows, along with production ...

Showing results 21-40

Data Preprocessing information

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 job categories do people searching Data Preprocessing jobs in Pennsylvania look for?

The top searched job categories for Data Preprocessing jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Data Preprocessing jobs?

Cities in Pennsylvania with the most Data Preprocessing job openings:

Clinical Data Scientist

Warrendale, PA โ€ข On-site, Remote

RedSail Technologies, LLC
Software Developmentย โ€ขย 51 - 200 employees

$140K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago


Key responsibilities

  • Gather and preprocess data from various sources to ensure data quality and reliability.

  • Analyze data through exploration, visualization, and statistical methods to identify patterns and insights.

  • Present findings and collaborate with stakeholders to support the development and evaluation of impactful programs.


Job description

Clinical Data ScientistJob Summary

The RedSail Advantage Solutions has the primary mission to create incremental value streams for RedSail through the development and activation of Clinical, Financial, & Operational Programs that leverage our uniquely integrated technology platforms as well as our associated reach within the targeted market segments. The Clinical Data Scientist, will participate in the making use of RedSail’s data to evaluate and establish various impactful programs to accomplish and assist with the measurement of program effectiveness against the department objectives.

Key Duties
  • Data Collection: Gathering data from various sources, such as databases, APIs, web scraping, and more. This can involve collecting structured and unstructured data.
  • Data Cleaning: Preprocessing the collected data to handle missing values, remove duplicates, correct inconsistencies, and address outliers. This step ensures data quality and reliability.
  • Data Exploration (Exploratory Data Analysis, EDA): Analyzing the main characteristics of the data often through visualization and summary statistics. This helps in understanding data distributions, relationships between variables, and identifying patterns or anomalies.
  • Data Transformation: Modifying data into a suitable format for analysis, such as normalization, standardization, or creating new features (feature engineering).
  • Data Visualization: Creating visual representations of data, such as graphs, charts, and dashboards, to communicate findings effectively. Tools like Matplotlib, Seaborn, and Tableau are commonly used.
  • Statistical Analysis: Applying statistical methods to understand data distributions, test hypotheses, and infer relationships. This can include t-tests, chi-square tests, ANOVA, and regression analysis.
  • Data Communication: Presenting findings, insights, and recommendations to stakeholders through reports, presentations, and storytelling. Effective communication is crucial for decision-making.
  • Collaboration with Domain Experts: Working with professionals from various fields to ensure that the data science approach aligns with business goals and that the results are meaningful and actionable.
  • Keeping Up with Industry Trends: Continuously learning and adapting to new tools, technologies, and methodologies in data science to stay current and effective in the field.
  • Ethical Considerations and Compliance: Ensuring that data usage complies with ethical standards and legal regulations, such as data privacy laws (e.g., HIPAA)
Education/Training
  • Bachelor’s degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree. Doctor of Pharmacy with data credentials or extensive data experience may substitute for formal education in Data Science.
Required Work Skills/Experience
  • Pharma/Pharmacy/Healthcare experience.
  • Experience programming with SQL scripting.
  • Experience with data analytics visualization tools such as PowerBI and Tableau.
  • Ability to transform complex data across multiple platforms into concise datasets.
  • Ability to visualize data in the most effective way possible for a given project or study.
  • Strong analytical and problem-solving skills; inquisitive.
  • Ability to work independently and with team members from different backgrounds and collaborative styles.
  • Excellent attention to detail with critical thinking skills.
Preferred Work Skills/Experience
  • A combination of both Doctor of Pharmacy and degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree (i.e. Pharmacist Data Scientist) strongly preferred.
  • 2 years of experience as a Data Analyst, Data Scientist or Data Engineer.
  • Experience with Pharma/Pharmacy transactions.
  • Experience programming with Python or Go Lang.
Discretionary Judgement
  • Uses independent judgment and discretion based upon the employee’s experience in the position and knowledge of the products, equipment, and services.
  • Uses good judgment and possesses ethical work values.
Physical Demands/Working Conditions/General Employment
  • Moderate or high stress levels may be experienced in the job performance.
  • Position is performed in a general office environment, home office, or approved remote workspace where physical work includes, but is not limited to, sitting, standing, reaching, kneeling, bending, and lifting to 25 lbs.
Equipment
  • Daily use of Microsoft Teams (phone), computer, printer, and other routine office equipment.
  • Must have reliable and consistent internet access.
Safety to Self and Others
  • Little responsibility for the safety of others. Job is performed in an office setting where there are no hazardous materials or equipment.
Working Conditions/Hazards
  • Position is performed in an open office environment or approved remote work location.
Compensation & Total Rewards
  • The anticipated base salary range for this position is $140,000-$145,000 annually. This position is also eligible for an annual target bonus of 4%. Actual compensation will be determined based on factors including relevant experience, skills, qualifications, and geographic location.
  • Benefits include paid time off, medical, dental, and vision insurance, a 401(k) with a 5% company match, a fitness bonus, professional development opportunities, and programs that support overall well-being.
Work Location
  • Hybrid at a RedSail Office
    • Spartanburg, SC
    • Irving, TX
    • Shreveport, LA
    • Oak Brook, IL
    • Cranberry Township, PA
    • Long Island, NY