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Machine Learning Part Time Jobs in Wisconsin (NOW HIRING)

Nursing Schedule: Part time, 32 hrs/wk, Days 7am-4pm Monday to Friday, no weekends, no on call, no ... machine-learning technologies, to assist with certain administrative aspects of the recruitment ...

Surgical Schedule: Part time, 16 hours per week. Day shift, start time 7AM or 10AM Facility: St ... machine-learning technologies, to assist with certain administrative aspects of the recruitment ...

Imaging Schedule: Part time, 28 hrs/wk, days 7am-330pm (8hr shifts) - no weekends, no on call and ... machine-learning technologies, to assist with certain administrative aspects of the recruitment ...

... part-time colleagues. * Paid Time Off (PTO) combines vacation, sick, and personal days into one ... machine-learning technologies, to assist with certain administrative aspects of the recruitment ...

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Machine Learning Part Time information

What is a Machine Learning Part Time job?

A Machine Learning Part Time job is a role where individuals work on ML-related tasks with a flexible or reduced schedule. These roles can involve data preprocessing, model development, evaluation, or deployment, depending on the organization's needs. Part-time positions are often suitable for students, freelancers, or professionals looking to gain experience while managing other commitments. They may be remote or on-site and can vary in duration and workload.

What are the key skills and qualifications needed to thrive in the Machine Learning Part Time position, and why are they important?

To thrive as a Machine Learning Part Time professional, you need a strong foundation in statistics, programming (often Python or R), and knowledge of core machine learning algorithms, typically demonstrated through a degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow, Scikit-learn, or PyTorch and experience with data preprocessing tools or cloud platforms are commonly expected, and certifications like TensorFlow Developer can be beneficial. Effective communication, time management, and the ability to work independently are key soft skills for success in this role. These competencies enable you to efficiently contribute to projects, solve complex problems, and collaborate remotely or in hybrid team environments.

What are the typical responsibilities and expectations for a part-time machine learning role?

In a part-time machine learning position, you are generally expected to assist with data preprocessing, model development, and analysis of project results under the guidance of a senior data scientist or engineer. Your tasks might include cleaning datasets, coding algorithms, running experiments, and preparing reports or presentations for team meetings. The work is often project-based and requires regular communication with team members to ensure alignment on objectives and deliverables. This structure allows you to gain hands-on experience with real-world datasets and industry tools while maintaining a flexible schedule, making it ideal for students or professionals transitioning into the field.
What are the most commonly searched types of Machine Learning jobs in Wisconsin? The most popular types of Machine Learning jobs in Wisconsin are:
What are popular job titles related to Machine Learning Part Time jobs in Wisconsin? For Machine Learning Part Time jobs in Wisconsin, the most frequently searched job titles are:
Infographic showing various Machine Learning Part Time job openings in Wisconsin as of May 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution.

Registered Nurse - Cardiac Rehab

Hshs

Green Bay, WI

$36.50 - $55.50/hr

Part-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Job description

Pay Range:

$36.50 - $55.50

A successful candidate's actual pay rate will be based on several factors including relevant experience, skills, training, certifications and education.

HSHS St. Mary's and St. Vincent Hospitals are seeking a Registered Nurse (RN) to join our Cardiac Rehabilitation team. Ideal candidates are patient-focused, mission-driven individuals dedicated to providing high-quality nursing care and education to patients recovering from cardiovascular events and procedures.
Position Specifics:
Department: Cardiac Rehab
Core Function: Nursing
Schedule: Part time, 32 hrs/wk, Days 7am-4pm Monday to Friday, no weekends, no on call, no holidays
Facility: St. Mary's Hospital and St.Vincent Hospital
Location: Green Bay, WI
Compensation aligned with your experience
For more questions contact Lauren Aman at lauren.aman@hshs.org

Education

Bachelors-Nursing - Preferred

Experience

Experience preferred

Certifications Licenses and Registrations

Certification in area of specialty - Preferred

Licensed in the state of practice-Required

Basic Life Support (BLS)-Required

Alias Titles

RN | Registered Nurse

Scheduled Weekly Hours:

32

Throughout communities in Illinois and Wisconsin, 13 hospitals, numerous community-based health centers and clinics, our 13,000+ colleagues have built a culture based on our solid core values of respect, care, competence, and joy. These are the ideals we believe in, work by, and live each day.

Built upon more than 145 years of service to the communities we serve, we now look to the future and our place in it as a health care system that strives to continually improve processes, procedures, and outcomes with the latest and most advanced technologies and treatments.

Regardless of how far our passion for excellence carries us, our focus will always remain on the most important person in our entire organization: The patient.

Benefits: HSHS provides a benefits package designed to support the overall well-being of our colleagues including their physical, emotional, financial, spiritual, and work health. Colleagues budgeted to work at least 32 hours per pay period are eligible for HSHS benefits.

  • Comprehensive and affordable health coverage includes medical, prescription, dental and vision coverage for full-time and part-time colleagues.

  • Paid Time Off (PTO) combines vacation, sick, and personal days into one balance to allow you the flexibility to use your time off as you need.

  • Retirement benefits including HSHS
    contributions.

  • Education Assistance benefits include up to $5,250 of educational assistance each calendar year and tuition discounts to select colleges with no waiting period.

  • Adoption Assistance provides financial support up to $7,500 for colleagues growing their families through adoption to reimburse application and legal fees, transportation, and more!

  • Other benefits include: Wellness program with incentives, employer-paid life insurance and short-term and long-term disability coverage, flexible spending accounts, employee assistance program, ID theft coverage, colleague rewards and recognition program, discount program, and more!

Benefits

HSHS and affiliates is an Equal Opportunity Employer (EOE).

HSHS is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.

Notice Regarding Potential Use of Artificial Intelligence in the Hiring Process

Hospital Sisters may use automated tools, including artificial intelligence or machine-learning technologies, to assist with certain administrative aspects of the recruitment process. These tools may help our recruiting team organize applications, search for resumes, identify qualifications reflected in application materials, and facilitate communications or scheduling with applicants.

Information used by these tools may include materials you provide during the application process, such as your resume, work history, education, qualifications, and responses to application questions.

These tools are used only to support our recruiting process. Hiring decisions are made by HSHS personnel, and automated tools do not make employment decisions on behalf of HSHS.

Applicants who have questions about this notice or who require a reasonable accommodation or alternative evaluation method may contact HSHS Human Resources at Contact@hshs.org