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Remote Machine Learning Finance Jobs in Lewisburg, PA

Geisinger Health

Application Developer Senior

Danville, PA · On-site +1

$109K - $151K/yr

... OCR, machine learning, document understanding, analytics, and intelligent automation platforms. Work is typically performed in an office or remote environment. Accountable for satisfying all job ...

Geisinger Health

Agile Delivery Lead

Danville, PA · On-site +1

... an office or remote environment. Accountable for satisfying all job specific obligations and ... Prior experience supporting AI, data science, or machine learning product teams * Exposure to Epic ...

Geisinger Health

Senior AI Product Manager

Danville, PA · On-site +1

$144K - $191K/yr

... an office or remote environment. Accountable for satisfying all job specific obligations and ... Machine Learning (ML), Vendor Evaluations OUR PURPOSE & VALUES: Everything we do is about caring ...

All JobsMachine Learning Finance JobsRemote Machine Learning Finance JobsRemote Machine Learning Finance Jobs in Lewisburg, PA

Remote Machine Learning Finance information

See Lewisburg, PA salary details

$22.3K

$82.5K

$120.7K

How much do remote machine learning finance jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote machine learning finance in Lewisburg, PA is $82,529.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,800.00 and $97,100.00 per year, depending on experience, location, and employer.

What is a remote machine learning finance professional?

A Remote Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems, often from a remote location. Professionals in this field develop models to predict market trends, assess risks, automate trading, or detect fraud using large datasets. Remote roles allow employees to work from anywhere, collaborating with teams virtually and using cloud-based tools to analyze data. These positions typically require strong programming skills, knowledge of finance, and experience with machine learning frameworks.

How do remote machine learning finance professionals typically collaborate with cross-functional teams?

Remote machine learning professionals in finance often work closely with data analysts, financial experts, and software engineers to develop and deploy predictive models. Collaboration is typically facilitated through virtual meetings, shared documentation, and project management tools. Clear communication and regular check-ins are crucial for aligning goals and ensuring that machine learning solutions address real business needs. Many organizations also encourage participation in virtual workshops and code reviews to maintain a strong sense of teamwork despite the remote setting.

What are the key skills and qualifications needed to thrive as a remote machine learning finance professional?

To excel in Remote Machine Learning Finance, strong analytical skills, a solid background in statistics or mathematics, and experience with financial data are essential, often supported by a degree in computer science, finance, or a related field. Familiarity with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or Scikit-learn), and knowledge of financial modeling tools are typically required. Excellent problem-solving, communication, and the ability to work independently are standout soft skills in this remote environment. These abilities are crucial for developing effective financial models, interpreting complex data, and collaborating with distributed teams to drive business value.

What cities near Lewisburg, PA are hiring for Remote Machine Learning Finance jobs?

Cities near Lewisburg, PA with the most Remote Machine Learning Finance job openings:

Remote Machine Learning Finance jobs near you
Infographic showing various Remote Machine Learning Finance job openings in Lewisburg, PA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $82,529 per year, or $39.7 per hour.

Data Scientist Senior (Population Health)

Geisinger Health

Danville, PA • On-site, Remote

Full-time

Medical, Dental, Vision

Re-posted 23 days ago

Geisinger Health rating

6.9

Company rating: 6.9 out of 10

Based on 447 frontline employees who took The Breakroom Quiz

456th of 891 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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