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Machine Learning Assistant Jobs in Philadelphia, PA

Acelero Learning

Executive Assistant

Philadelphia, PA · On-site

$76K/yr

Data-Informed Learning; Transparent & Open Communication; Growth Mindset; Championing Equality ... machine. - Files, stores, and destroys old records as instructed. - Coordinates purchase ...

Acelero Learning

Executive Assistant

Philadelphia, PA · On-site

$76K/yr

Data-Informed Learning; Transparent & Open Communication; Growth Mindset; Championing Equality ... machine. - Files, stores, and destroys old records as instructed. - Coordinates purchase ...

Eisneramper Llp

AI Consulting Manager

Conshohocken, PA · On-site

... machine learning, and emerging technologies to solve complex business challenges. This role is ... * Assist in developing AI strategies, roadmaps, and solution recommendations aligned with client ...

Eisneramper Llp

AI Consulting Manager

Philadelphia, PA · On-site

... machine learning, and emerging technologies to solve complex business challenges. This role is ... * Assist in developing AI strategies, roadmaps, and solution recommendations aligned with client ...

Athenago

Data Science Intern

Wilmington, DE

We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ... Strong foundation in statistics and machine learning concepts (regression, classification ...

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All JobsMachine Learning JobsMachine Learning Assistant JobsMachine Learning Assistant Jobs in Philadelphia, PA

Machine Learning Assistant information

See Philadelphia, PA salary details

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How much do machine learning assistant jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for machine learning assistant in Philadelphia, PA is $18.22, according to ZipRecruiter salary data. Most workers in this role earn between $16.49 and $19.42 per hour, depending on experience, location, and employer.

What is a machine learning assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

What are the key skills and qualifications needed to thrive as a machine learning assistant?

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

What are some common challenges a machine learning assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What are the most commonly searched types of Machine Learning jobs in Philadelphia, PA?

The most popular types of Machine Learning jobs in Philadelphia, PA are:

What are popular job titles related to Machine Learning Assistant jobs in Philadelphia, PA?

For Machine Learning Assistant jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Assistant jobs in Philadelphia, PA look for?

The top searched job categories for Machine Learning Assistant jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Machine Learning Assistant jobs?

Cities near Philadelphia, PA with the most Machine Learning Assistant job openings:

Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 25% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $37,891 per year, or $18.2 per hour.

Healthcare Data Scientist & AI Solutions

BioVid

Bristol, PA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

BioVid is transforming pharmaceutical market research by replacing slow, traditional methodologies with AI-augmented data systems.

In this role, you will personally analyze the data to uncover HCP prescribing behavior and behavioral insights. You will help bridge quantitative real-world data with qualitative market research, and play a key role in developing synthetic audiences (“Digital Twins”) that mirror healthcare provider prescribing behavior and patient treatment journeys, while enabling scalable forecasting, segmentation, and market intelligence solutions.


Must-Have Qualifications


Hands-on analysis of medical / pharmacy claims data (EHR preferred)

Direct, hands-on experience analyzing the data itself — not only engineering it. You can extract and predict HCP prescribing behavior for specific drugs, for specific conditions, in specific treatment areas, and tag HCP qualitative / attitudinal segments to NPIs, associating those segments with real prescribing behavior. HIPAA requirements fluent (most of our data will be deidentified)

  • Analyze medical and pharmacy claims to extract and predict HCP prescribing behavior for specific drugs, conditions, and treatment areas.
  • Perform HCP / patient segmentation, demand forecasting, journey mapping, modeling
  • Help build Synthetics, simulated segments and HCP equivalents.
  • Machine Learning experience in modeling training and evaluating models (LLM fine tuning, training a nice to have)
  • Tag qualitative / attitudinal HCP segments to NPIs and link them to observed prescribing behavior.
  • Translate these analyses into actionable segmentation, targeting, and forecasting insights.


Data Cleaning, Processing, Augmentation and Transformation

  • Data cleaning, scarcity, gap analysis, joining and data augmentation, transformation to create partitions, data marts and analytics workspaces for analysis and modeling in AWS/Athena.

Key Responsibilities


Data Integration & Modeling

  • Data cleaning, scarcity, gap analysis, joining and data augmentation, transformation to create partitions, data marts and analytics workspaces for analysis and modeling inAWS/Athena.
  • Resolve identity matching, tokenization, and data harmonization challenges across disparate sources.
  • Build scalable, tested, and version-controlled data models using dbt on AWS/Athena.


Data Quality, Governance & Compliance

  • Implement automated data quality checks using tools such as Great Expectations or equivalent.


Analytics, AI & Machine Learning

  • Conduct advanced exploratory data analysis (EDA) and feature engineering using SQL, Python, pandas, and numpy.
  • Analyze claims data to model and predict HCP prescribing behavior by drug, condition, and treatment area, and associate attitudinal segments with NPIs.
  • Build AI-powered synthetic provider and patient personas grounded in real-world claims distributions.
  • Develop methods to scale qualitative research insights into national quantitative projections.
  • Machine Learning experience in modeling training and evaluating models. (LLM fine tuning and training a nice to have
  • Perform (or help perform) and automate pharmaceutical market research including:
  • HCP segmentation
  • Demand forecasting
  • Patient journey mapping
  • Audience simulation


API & Product Delivery

  • Build and maintain performant backend APIs using FastAPI, deployed on AWS (e.g., ECS/Fargate, App Runner, or Lambda).
  • Deliver data products, personas, and insights to internal tools and client-facing applications.


Skills & Experience

  • 5+ years in Analytics Engineering, Data Engineering, Data Science, or similar roles.
  • Proven ownership of end-to-end data pipelines and scalable analytics systems on AWS.
  • Hands-on experience with AWS data and analytics tooling, including Athena, S3, Glue, and SageMaker (AWS is the primary environment).
  • Strong experience with healthcare claims and EHR data (Rx, Dx, medical, pharmacy) and major data vendors such as IQVIA, Komodo, Symphony, or Definitive Healthcare.
  • Demonstrated hands-on analysis of medical/pharmacy claims to extract and predict HCP prescribing behavior and tag attitudinal segments to NPIs.
  • Expert SQL and strong Python skills, including pandas and large-scale data workflows.
  • Understanding of pharma market research, including patient journeys, HCP segmentation, and demand modeling.
  • Experience integrating survey or primary research data with large quantitative datasets.
  • Comfortable using AI coding assistants and agentic development tools to accelerate delivery.

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