1

Temporary Machine Learning Scientist Jobs in Northbrook, IL

Machine Learning Engineer

Chicago, IL · On-site

$100 - $125/hr

Advanced degree in a Science, Technology, Engineering, or Mathematics field required * Typically requires a minimum of two years of hands‑on industry experience in machine learning, computer vision ...

Machine Learning Engineer

Chicago, IL · On-site

$95K - $138K/yr

Advanced degree in a Science, Technology, Engineering, or Mathematics field required * Typically requires a minimum of two years of hands-on industry experience in machine learning, computer vision ...

Machine Learning Tutor

Wheaton, IL · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Chicago, IL · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Skokie, IL · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional ... Partner closely with Data Scientists to support traditional ML model development, including feature ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

next page

Showing results 1-20

Temporary Machine Learning Scientist information

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a temporary machine learning scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What are popular job titles related to Temporary Machine Learning Scientist jobs in Northbrook, IL?

For Temporary Machine Learning Scientist jobs in Northbrook, IL, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Scientist jobs in Northbrook, IL look for?

The top searched job categories for Temporary Machine Learning Scientist jobs in Northbrook, IL are:

What cities near Northbrook, IL are hiring for Temporary Machine Learning Scientist jobs?

Cities near Northbrook, IL with the most Temporary Machine Learning Scientist job openings:

Infographic showing various Temporary Machine Learning Scientist job openings in Northbrook, IL as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 27% Part Time, 1% Temporary, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer

Moody

Chicago, IL • On-site

$100 - $125/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Job description

Let's begin! Machine Learning Engineer (14907)

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.


Employment eligibility to work in the U.S. is required, as Moody’s will not pursue visa sponsorship for this position


Skills and Competencies



  • Expertise in Python programming, including machine learning libraries such as NumPy, Pandas, and PyTorch

  • Experience with machine learning operations practices, including continuous integration and continuous deployment pipelines, model monitoring, and model maintenance preferred

  • Expertise with modern machine learning tools and platforms, including Jupyter, Docker, Git, and cloud computing environments such as Amazon Web Services or Google Cloud Platform

  • Experience building data tools for extract, transform, and load processes, extracting data from SQL and NoSQL databases, and conducting advanced data analysis

  • Experience with geographic information systems preferred

  • Excellent written and verbal communication skills, with the ability to understand and articulate business requirements and objectives to both technical and non-technical stakeholders

  • Expertise in supervised and unsupervised machine learning algorithms and their implementations, including advanced concepts such as active learning, computer vision, and deployments in complex environments

  • Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization


Education



  • Advanced degree in a Science, Technology, Engineering, or Mathematics field required

  • Typically requires a minimum of two years of hands‑on industry experience in machine learning, computer vision, data science, or a related field


Responsibilities


Develop practical, scalable, and robust machine learning and computer vision solutions that enhance product capabilities and deliver value to clients.



  • Collect, clean, preprocess, and analyze data to support machine learning model development and maximize data value

  • Create visualizations and conduct exploratory analysis to identify patterns, trends, opportunities, and data quality issues

  • Train, evaluate, refine, and deploy machine learning models aligned with business objectives and product requirements

  • Design, implement, and automate large-scale model training, integration, and evaluation pipelines

  • Collaborate with machine learning, software engineering, product development, sales, and cross-functional stakeholders to deliver innovative solutions

  • Communicate technical findings and recommendations to both technical and non-technical audiences through clear documentation and presentations

  • Design and execute experiments to validate assumptions, improve model performance, and support data-driven decision making

  • Ensure projects follow governance, security, ethical AI, and responsible data use practices while identifying and resolving operational inefficiencies


About the Team


Our Machine Learning Technology team is responsible for the core technology behind award-winning property intelligence solutions. We leverage machine learning, geospatial imagery, and computer vision to measure and monitor the built environment while delivering actionable insights to clients. By joining our team, you will contribute to innovative work that helps organizations better understand how homes and workplaces can withstand evolving climate and economic risks, while advancing the responsible adoption of artificial intelligence across our products and solutions.


For US-based roles only: the anticipated hiring base salary range for this position is$95,500.00-$138,550.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody’s also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.


Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status,sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email accommodations@moodys.com . This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications


For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.


This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.


Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

#J-18808-Ljbffr