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Volunteer Data Analyst Machine Learning Jobs in Pennsylvania

Compunnel

Machine Learning Engineer

Philadelphia, PA · On-site

The role focuses on the end-to-end Machine Learning lifecycle, including data engineering, model development, offline evaluation, production deployment, monitoring, retraining, and A/B testing. The ...

TeleTracking

Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

They are seeking a Senior Machine Learning Engineer to develop and optimize machine learning models ... analytics for patient outcomes. • Build and optimize data ingestion and modeling pipelines as ...

Cmu

Data Scientist

Pittsburgh, PA

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

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All JobsVolunteer Data Analyst Machine Learning JobsVolunteer Data Analyst Machine Learning Jobs in Pennsylvania

Volunteer Data Analyst Machine Learning information

What is the difference between Volunteer Data Analyst Machine Learning vs Volunteer Data Analyst?

AspectVolunteer Data Analyst Machine LearningVolunteer Data Analyst
Required skillsData analysis, machine learning, programming (Python/R), statistical knowledgeData analysis, Excel, basic statistics, data visualization
Work environmentTech-focused, project-based, collaborative teamsNon-profit, research, community projects
Common employersTech companies, research institutions, startupsNon-profits, NGOs, community organizations

Volunteer Data Analyst Machine Learning roles typically require programming and machine learning expertise, working on advanced data projects. Volunteer Data Analysts focus on data cleaning, visualization, and basic analysis. Both roles support organizations but differ in technical complexity and scope.

What are the most commonly searched types of Data Analyst Machine Learning jobs in Pennsylvania?

The most popular types of Data Analyst Machine Learning jobs in Pennsylvania are:

Volunteer Data Analyst Machine Learning jobs near you

Principal Machine Learning Engineer

Apetan Consulting llc

Philadelphia, PA • On-site

$80 - $150/hr

Contractor

Re-posted 4 days ago

Job description

Title: Principal Machine Learning Engineer

Duration: 6 Mos C2H (without sponsorship)

Location: Hybrid in Philadelphia, PA onsite Tue & Wed each week (Local candidates preferred but, those willing to relocate are acceptable)

Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning, predictive modeling, scoring, decisioning, and applied AI initiatives. This role will primarily focus on building, validating, deploying, and improving machine learning models, while also bringing principal-level judgment to problem definition, model design, stakeholder engagement, and production readiness.

Hands-On Model Development

  • Build, test, validate, and improve machine learning models for scoring, prediction, prioritization, risk detection, engagement, intervention targeting, and decision support.
  • Perform exploratory data analysis, data quality assessment, feature engineering, model training, model selection, and performance evaluation.
  • Develop practical ML models that balance predictive performance, explainability, stability, maintainability, and business usefulness.
  • Work with structured, semi-structured, and operational data to create model-ready datasets and reusable features.
  • Use tools such as Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, or similar platforms and libraries.
  • Move quickly from data exploration to prototype to validated model to production-ready capability.

 

Required Qualifications

  • Professional experience in machine learning, data science, software engineering, analytics engineering, applied AI, or related technical fields.
  • 5+ years of hands-on machine learning model development experience, including feature engineering, model training, validation, evaluation, and iteration.
  • 3+ years of experience deploying, operationalizing, or supporting models in production or business-critical environments.
  • Strong hands-on experience with Python and SQL.
  • Experience with modern ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, AWS, or similar technologies.
  • Strong understanding of model evaluation, calibration, thresholding, score interpretation, monitoring, drift, retraining, and production ML lifecycle management.
  • Experience translating ambiguous business problems into concrete ML designs, model requirements, validation plans, and measurable outcomes.
  • Ability to explain model behavior, model performance, assumptions, limitations, and tradeoffs to both technical and non-technical stakeholders.
  • Strong engineering discipline, including clean code, reproducibility, versioning, testing, documentation, and maintainability.
  • Ability to work independently as a senior hands-on contributor while also providing technical leadership and modeling judgment.

Scoring, Scorecards, and Transparent Models

Production ML and MLOps

Product and Rapid-Build Execution

Generative AI and AI Automation

Requirement Shaping and Stakeholder Partnership