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Remote Machine Learning Robotics Jobs in Pennsylvania

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks for ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... machine learning and multipoint geostatistics for characterization of fractures and novel ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Experiences with machine learning is a plus to the application. * Solid understanding of the ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... The work will involve research on machine learning, digital twins, electronic design automation ...

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Qualified candidates are expected to have a background in scientific machine learning,numerical ...

Deckers

Sr. Manager, Data & ML Engineering

Indiana, PA · Remote

United States (Remote) Interested applicants must reside in one of the following approved states ... Enable future machine learning use cases by ensuring curated datasets are ML-ready, including ...

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Remote Machine Learning Robotics information

What is a Remote Machine Learning Robotics job?

A Remote Machine Learning Robotics job involves developing and implementing machine learning algorithms to control and improve robotic systems, all while working from a remote location. Professionals in this field use artificial intelligence techniques to enable robots to learn from data and adapt to new tasks. They collaborate with teams virtually, leveraging cloud-based tools and simulation environments to design, test, and deploy robotic solutions. This role typically requires strong programming skills, knowledge of robotics frameworks, and experience with machine learning models.

What is the difference between Remote Machine Learning Robotics vs Remote Data Scientist?

AspectRemote Machine Learning RoboticsRemote Data Scientist
Required CredentialsDegree in Robotics, Computer Science, or related fields; experience with ML algorithms and robotics platformsDegree in Data Science, Statistics, or related fields; proficiency in ML, statistics, and programming
Work EnvironmentHands-on with robotics hardware, simulation environments, and software developmentData analysis, modeling, and visualization primarily on software platforms
Employer & Industry UsageRobotics companies, manufacturing, autonomous vehicles, research labsTech firms, finance, healthcare, research institutions

Remote Machine Learning Robotics focuses on developing intelligent systems that integrate robotics hardware with machine learning algorithms, often requiring hands-on hardware work. In contrast, Remote Data Scientists primarily analyze data and build models using software tools. Both roles involve ML expertise but differ in work environment and industry applications.

How do remote machine learning robotics professionals typically collaborate with hardware teams when working off-site?

Remote machine learning robotics professionals often collaborate closely with hardware teams through regular virtual meetings, shared documentation, and cloud-based development environments. They use simulation tools to test algorithms before deployment and rely on video calls or live streams to observe hardware tests in real time. Effective communication and detailed feedback are essential to ensure that software and hardware integration runs smoothly, despite working from different locations. This collaborative approach helps address issues quickly and keeps projects on track.

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

To thrive as a Remote Machine Learning Robotics Engineer, you need a solid background in robotics, machine learning algorithms, programming (Python, C++), and typically a degree in computer science, robotics, or a related field. Familiarity with robotics frameworks (like ROS), machine learning libraries (such as TensorFlow or PyTorch), and experience with cloud platforms or remote collaboration tools are highly valued. Strong problem-solving abilities, initiative, and effective remote communication skills help you excel in distributed teams. These competencies enable you to develop intelligent robotic systems efficiently, collaborate across locations, and drive innovation in a rapidly evolving field.
What are popular job titles related to Remote Machine Learning Robotics jobs in Pennsylvania? For Remote Machine Learning Robotics jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Robotics jobs in Pennsylvania look for? The top searched job categories for Remote Machine Learning Robotics jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Remote Machine Learning Robotics jobs? Cities in Pennsylvania with the most Remote Machine Learning Robotics job openings:
Remote Machine Learning Robotics jobs near you
Data Scientist Senior (Population Health)

Data Scientist Senior (Population Health)

Geisinger Health

Danville, PA • On-site, Remote

Full-time

Medical, Dental, Vision

Posted 15 days ago

Geisinger Health rating

6.9

Company rating: 6.9 out of 10

Based on 436 frontline employees who took The Breakroom Quiz

446th of 882 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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