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Internship Medical Data Encoder Jobs in California

WEA CA PC

Internship Coordinator

Los Angeles, CA

$27.88 - $36.06/hr

Position Overview The Graduate Internship Coordinator serves as the organizational hub for all ... medical center * Bilingual or multilingual abilities * Experience with program evaluation, data ...

Stryker

$35/hr

... medical technologies. As an intern, you won't just observe -- you'll contribute to meaningful ... Interns who propose innovative ideas and consistently exceed their performance objectives. Customer ...

Stryker

$35/hr

... medical technologies. As an intern, you won't just observe -- you'll contribute to meaningful ... Interns who propose innovative ideas and consistently exceed their performance objectives. Customer ...

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Internship Medical Data Encoder information

What is an internship medical data encoder?

An Internship Medical Data Encoder is a student or recent graduate who assists in converting medical information from patient records into standardized codes used for billing, insurance, and data analysis. This role is typically an entry-level position within healthcare organizations, offered as part of a practical learning experience. Interns learn to use coding systems such as ICD-10 and CPT, work with electronic health records, and ensure the accuracy and confidentiality of patient data. The internship provides valuable hands-on experience and can be a stepping stone to a full-time medical coding or health information management career.

What are the key skills and qualifications needed to thrive as an internship medical data encoder?

To thrive as an Internship Medical Data Encoder, you need attention to detail, strong organizational skills, and a basic understanding of medical terminology, often supported by coursework in health information management or related fields. Familiarity with electronic health record (EHR) systems, medical coding software (such as ICD-10 or CPT codes), and data entry tools is typically required. Excellent communication, time management, and the ability to maintain confidentiality are key soft skills for this position. These competencies ensure accurate data processing, support healthcare operations, and uphold patient privacy standards.

What are some common challenges faced by an internship medical data encoder, and how can they be addressed?

Internship Medical Data Encoders often encounter challenges such as accurately interpreting complex medical terminology and ensuring that data is entered consistently according to specific coding standards. Managing large volumes of patient records while maintaining a high level of attention to detail can also be demanding. To address these challenges, interns should familiarize themselves with coding guidelines, seek clarification from supervisors when uncertain, and utilize available reference materials and software tools. Regular feedback and collaboration with experienced team members can further help interns develop their accuracy and efficiency.

What are the most commonly searched types of Medical Data Encoder jobs in California?

The most popular types of Medical Data Encoder jobs in California are:

What are popular job titles related to Internship Medical Data Encoder jobs in California?

For Internship Medical Data Encoder jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Medical Data Encoder jobs in California look for?

The top searched job categories for Internship Medical Data Encoder jobs in California are:

What cities in California are hiring for Internship Medical Data Encoder jobs?

Cities in California with the most Internship Medical Data Encoder job openings:

Internship Medical Data Encoder jobs near you
Infographic showing various Internship Medical Data Encoder job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Senior Lead ML Encoder

South San Francisco, CA • On-site

Dawar Consulting, Inc.
IT Services • 11 - 50 employees
Learn more about Dawar Consulting, Inc.external

$150 - $200/hr

Other

Medical, Retirement

Posted 7 days ago

Job description

Senior ML Encoder

South San Francisco, United States | Posted on 08/26/2026

Our client, a world leader in biotechnology and life sciences, is looking for a \"Senior ML Encoder\".

Job Duration: Long-Term Contract (Possibility Of Extension)

Company Benefits: Medical, Paid Sick Leave, 401 (k)

Seeking a senior ML Encoder Lead to develop shared customer representations from longitudinal transaction, sales, and interaction data. The ideal candidate will independently define modeling objectives, build and evaluate encoder/embedding models, develop production-ready code, and determine whether the approach provides meaningful downstream value.

Required Skills & Qualifications
  • Proven experiencepersonally training encoder or embedding modelsand designing pretraining objectives.
  • Deep expertise inrepresentation learning, including self-supervised/contrastive learning, sequence/temporal modeling, transformers, GNNs, or recommender embeddings.
  • Experience with large-scale, sparse, longitudinal event data such as transactions, clickstreams, customer journeys, or engagement histories.
  • Experience developinginductive representationsfor entities with limited historical data.
  • Strong model evaluation skills, including time-based splits, leakage detection, cold-start analysis, uncertainty, and robust baselines.
  • Ability to evaluate embeddings forincremental signal, calibration, stability, drift, and subgroup performance.
  • StrongPythonskills withPyTorch or JAX, SQL, distributed data processing, and cloud-based model training.
  • Experience taking ML models from research to production, including pipelines, data contracts, versioning, serving, monitoring, and reproducibility.
  • Strong communication skills with the ability to present findings, uncertainty, and recommendations to senior stakeholders.
Preferred Skills
  • Knowledge of privacy, fairness, and re-identification risks in learned representations.
  • Publications, patents, or public applied work in representation learning.
  • Experience with large-scale behavioral data in consumer technology, marketplaces, streaming, financial services, payments, or advertising technology.
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