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Remote Machine Learning Postdoc Jobs in Pennsylvania

Maximus

AI/ML Software Developer

Erie, PA · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... Prepares and structures data for machine learning pipelines, feature engineering, and model ...

Maximus

AI/ML Software Developer

West Chester, PA · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... Prepares and structures data for machine learning pipelines, feature engineering, and model ...

Maximus

AI/ML Software Developer

Allentown, PA · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... Prepares and structures data for machine learning pipelines, feature engineering, and model ...

Maximus

AI/ML Software Developer

Bloomsburg, PA · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... Prepares and structures data for machine learning pipelines, feature engineering, and model ...

Maximus

AI/ML Software Developer

Harrisburg, PA · Remote

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... Prepares and structures data for machine learning pipelines, feature engineering, and model ...

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Remote Machine Learning Postdoc information

Is ML a high paying job?

Machine learning postdoctoral positions are generally well-paid compared to many academic roles, with salaries often ranging from $60,000 to over $100,000 annually depending on experience, location, and funding. These roles typically require strong programming skills in Python or R and knowledge of algorithms and data analysis, which can contribute to higher compensation levels.

Is a PhD in ML worth it?

A PhD in machine learning can enhance qualifications for a remote machine learning postdoc position, often leading to higher-level research opportunities and increased earning potential. However, it requires significant time investment and may not be necessary for industry roles that value practical skills and experience with tools like Python and TensorFlow. The decision depends on career goals and the specific requirements of the desired position.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Postdoc, and why are they important?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

Is a postdoc harder than a PhD?

A remote machine learning postdoc typically involves more specialized research, higher expectations for independence, and often requires advanced skills in programming and data analysis. While a PhD focuses on completing a dissertation and gaining foundational expertise, a postdoc emphasizes producing publishable research and may involve longer hours and greater responsibility, making it generally more demanding in terms of research output and expertise. However, the difficulty varies based on individual experience and research environment.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

Do you need H-1B for postdoc?

A remote machine learning postdoctoral position typically does not require H-1B sponsorship if the candidate is already authorized to work in the country, such as through a visa or citizenship. However, international candidates may need H-1B or other work visas depending on the employer and local immigration laws. Employers often sponsor visas for postdocs to comply with legal requirements and facilitate employment.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
What are the most commonly searched types of Machine Learning Postdoc jobs in Pennsylvania? The most popular types of Machine Learning Postdoc jobs in Pennsylvania are:
What are popular job titles related to Remote Machine Learning Postdoc jobs in Pennsylvania? For Remote Machine Learning Postdoc jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Pennsylvania look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Remote Machine Learning Postdoc jobs? Cities in Pennsylvania with the most Remote Machine Learning Postdoc job openings:
Remote Machine Learning Postdoc jobs near you
Infographic showing various Remote Machine Learning Postdoc job openings in Pennsylvania as of July 2026, with employment types broken down into 67% Full Time, 11% Part Time, and 22% Contract. Highlights an 100% Remote job distribution.
Data Scientist Senior (Population Health)

Data Scientist Senior (Population Health)

Geisinger Health

Danville, PA • On-site, Remote

Full-time

Medical, Dental, Vision

Re-posted 8 days ago

Geisinger Health rating

6.8

Company rating: 6.8 out of 10

Based on 434 frontline employees who took The Breakroom Quiz

483rd of 877 rated healthcare providers

Job description

Location:
Work from home (Pennsylvania)
Shift:
Days (United States of America)
Scheduled Weekly Hours:
40
Worker Type:
Regular
Exemption Status:
Yes
Job Summary:
The Senior Data Scientist is a strategic leader in our organization, driving the entire lifecycle of data science initiatives that directly impact healthcare outcomes. Leveraging your deep expertise and mastery of machine learning, you will spearhead the development, implementation, and evaluation of complex AI models in healthcare settings specifically population health. Your ability to translate technical concepts into actionable insights will empower stakeholders to make informed decisions that enhance patient care and operational efficiency. You will also play a crucial role in mentoring and developing junior data scientists and analysts, fostering a culture of data-driven innovation.
Job Duties:
  • Leads and manages the entire lifecycle of data science projects, from conceptualization and design to development, deployment, and ongoing optimization.
  • Build and deploy advanced analytics that explain and predict acute utilization (Inpatient/Emergency Department) and quantify how care delivery changes (e.g., panel shifts, capacity differences, continuity disruption) impact outcomes for heart failure and other high-risk populations.
  • Translate longitudinal patient care data into actionable intervention points across primary care, specialty care, and monitoring programs.
  • Partner with clinical and operational leaders to convert analytic findings into care pathway recommendations, operational triggers, and monitoring protocols; define measures of success and evaluate impact.
  • Collaborate with cross-functional teams to define project scope, objectives, analytic design, validation strategy, and expected impact, ensuring alignment with organizational goals and measurable improvements in healthcare outcomes.
  • Leverages deep understanding of machine learning algorithms to build patient-level and population-level models that support risk stratification, trajectory analysis, forecasting, capacity planning, and scenario analysis for diverse healthcare applications.
  • Utilizes clustering, dimension reduction, and deep generative models to uncover hidden patterns and insights within large, complex healthcare datasets.
  • Applies rigorous validation techniques to ensure model accuracy, stability, fairness, generalizability, and clinical usefulness across patient cohorts, sites, time periods, and operational settings.
  • Oversees the deployment of models into production environments, ensuring seamless integration with existing systems.
  • Extracts insights from clinical and operational data sources (Epic Clarity, HL7, and other enterprise data sources) to inform decision-making and guide project direction.
  • Translates complex technical findings into compelling narratives that resonate with non-technical stakeholders through presentations, dashboards, technical documentation, and stakeholder discussions.
  • Facilitates data-driven decision-making by effectively communicating the value and impact of AI models.
  • Mentors and guide junior data scientists, fostering their professional growth and technical expertise.
  • Promotes a culture of collaboration, knowledge sharing, and continuous learning within the data science team.
  • Contributes to developing best practices and standards for data science and machine learning within the organization.
  • Stays abreast of the latest advancements in machine learning and healthcare research to identify opportunities for improvement and innovation.
  • Experiments with new approaches and technologies to enhance model performance and expand the organization's data science capabilities.

Work is typically performed in an office or remote environment. Accountable for satisfying all job specific obligations and complying with all organization policies and procedures. The specific statements in this profile are not intended to be all-inclusive. They represent typical elements considered necessary to successfully perform the job.
*Relevant experience may be a combination of related work experience and degree obtained (Master's Degree = 2 years; PHD = 4 years ).
Position Details:
Preferred skills:
  • Databricks, Python, SQL, advanced statistical analysis, machine learning, emerging AI technologies and implementation (LLMs, RAG, GenAI, Agentic workflow integrations and deployment)
  • Healthcare experience preferably with Population Health initiatives
  • Familiarity with Epic Clarity, Caboodle, claims data, CMS/Medicare populations, or payer-provider analytics

Education:
Bachelor's Degree-Related Field of Study (Required)
Experience:
Minimum of 4 years-Relevant experience* (Required)
Certification(s) and License(s):
Skills:
Analytical Thinking, C++ Programming Language, Clinical Data Cleaning, Communication, Group Collaboration, Machine Learning Methods, Python (Programming Language), Statistical Methods, Structured Query Language (SQL)
OUR PURPOSE & VALUES: Everything we do is about caring for our patients, our members, our students, our Geisinger family and our communities.
  • KINDNESS: We strive to treat everyone as we would hope to be treated ourselves.
  • EXCELLENCE: We treasure colleagues who humbly strive for excellence.
  • LEARNING: We share our knowledge with the best and brightest to better prepare the caregivers for tomorrow.
  • INNOVATION: We constantly seek new and better ways to care for our patients, our members, our community, and the nation.
  • SAFETY: We provide a safe environment for our patients and members and the Geisinger family.

We offer healthcare benefits for full time and part time positions from day one, including vision, dental and domestic partners. Perhaps just as important, we encourage an atmosphere of collaboration, cooperation and collegiality.
We know that a diverse workforce with unique experiences and backgrounds makes our team stronger. Our patients, members and community come from a wide variety of backgrounds, and it takes a diverse workforce to make better health easier for all. We are proud to be an affirmative action, equal opportunity employer and all qualified applicants will receive consideration for employment regardless to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or status as a protected veteran.

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