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Remote Data Scientist

Jackson, MS · On-site +1

Proven experience in data science or a related field. * Proficiency in programming languages such ... Strong communication skills and the ability to work collaboratively in a remote environment. Salary ...

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Remote Data Science Apprenticeship information

What is a Remote Data Science Apprenticeship?

A Remote Data Science Apprenticeship is a structured training program that allows individuals to gain practical experience in data science while working from a remote location. These apprenticeships typically combine mentorship, hands-on projects, and coursework to help participants develop essential skills like data analysis, machine learning, and programming. Apprentices work with real-world datasets and collaborate with experienced data scientists, often as part of a distributed team. The remote format offers flexibility and accessibility, making it easier for people from various backgrounds to enter the data science field.

What are some common challenges faced during a remote data science apprenticeship, and how can they be overcome?

Remote data science apprenticeships often present challenges such as limited face-to-face mentorship, managing time across different projects, and staying motivated without in-person team dynamics. To overcome these, it's important to proactively communicate with your mentors and peers, make use of collaborative tools like Slack or Zoom, and set clear, achievable goals each week. Establishing a structured daily routine and regularly participating in virtual team meetings can also help maintain accountability and foster a sense of connection with the team.

What is the difference between Remote Data Science Apprenticeship vs Remote Data Analyst?

AspectRemote Data Science ApprenticeshipRemote Data Analyst
Required CredentialsTypically entry-level, often requiring a background in math, statistics, or computer science; may include certifications or coursesUsually requires a degree in data-related fields; certifications like Excel, SQL, or Tableau are common
Work EnvironmentTraining-focused, often with mentorship; may involve project-based learningOperational, analyzing data to support business decisions; may involve reporting and visualization
Employer & Industry UsageUsed by companies to train future data scientists; common in tech, finance, healthcareUsed across industries for data-driven decision making; common in marketing, finance, retail

The Remote Data Science Apprenticeship is a training program designed to develop skills in data science, often with mentorship, while a Remote Data Analyst focuses on analyzing and interpreting data to inform business strategies. Both roles require familiarity with data tools, but apprenticeships emphasize learning and growth, whereas analyst roles focus on applying existing skills.

What are the key skills and qualifications needed to thrive as a Remote Data Science Apprentice, and why are they important?

To thrive as a Remote Data Science Apprentice, you need a solid understanding of statistics, programming (commonly Python or R), and a relevant educational background such as coursework or a degree in computer science, mathematics, or a related field. Familiarity with data analysis tools like Pandas, NumPy, SQL, and visualization platforms, as well as version control systems such as Git, is typically required. Strong communication, problem-solving abilities, and self-motivation are essential soft skills for remote collaboration and continuous learning. These skills and qualities are crucial for effectively analyzing data, contributing to team projects, and adapting to the dynamic, independent nature of remote work environments.
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Remote Data Science Apprenticeship jobs near you
Infographic showing various Remote Data Science Apprenticeship job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 83% Full Time, 11% Part Time, 1% Contract, and 3% Nights. Highlights an 99% Physical, and 1% Remote job distribution.

Data Scientist nlp remote

ESRhealthcare and EXEC STAFF RECRUITERS

New York, NY • Remote

Full-time

Posted 8 days ago

Job description

Data Scientist nlp remote

Data Scientist to help revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

Youll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. Youll collaborate closely with cross-functional teams to:

Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If youre excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

Qualifications

3+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Proficiency with Python
Experience with the latest in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
Bonus Experience

Experience with document layout analysis (using vision, NLP, or both).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
Responsibilities

Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
After 3 Months, You Will

Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
After 1 Year, You Will

Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on models and a source from which other teams can seek information and recommendations.

Data Scientist nlp remote

Data Scientist to help revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

Youll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. Youll collaborate closely with cross-functional teams to:

Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If youre excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

Qualifications

3+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Proficiency with Python
Experience with the latest in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
Bonus Experience

Experience with document layout analysis (using vision, NLP, or both).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
Responsibilities

Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
After 3 Months, You Will

Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
After 1 Year, You Will

Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on Datavants models and a source from which other teams can seek information and recommendations.

Working Place:

NYC, New York, United States

Company
:


ESR Healthcare

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