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Temporary Data Scientist Machine Learning Jobs in Madison, WI

Abbott

Sr. Engineer, AI Platform

Madison, WI · On-site

$99K - $198K/yr

Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems. * Partner on the ...

Abbott

Sr. Engineer, AI Platform

Madison, WI · On-site

$99K - $198K/yr

Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems. * Partner on the ...

Abbott

Sr. Engineer, AI Platform

Madison, WI · On-site

$99K - $198K/yr

Collaborate closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems. * Partner on the ...

AgSource

Senior AI/ML Engineer

Madison, WI · On-site

$104K - $143K/yr

EDUCATION & EXPERIENCE Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical ...

AgSource

Senior AI/ML Engineer

Madison, WI · On-site +1

$104K - $143K/yr

EDUCATION & EXPERIENCE Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical ...

Urus

Senior AI/ML Engineer

Madison, WI · On-site

$104K - $143K/yr

EDUCATION & EXPERIENCE Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical ...

Urus Group LP

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

EDUCATION & EXPERIENCE Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical ...

Farm Systems

Senior AI/ML Engineer

Madison, WI · On-site

$104K - $143K/yr

EDUCATION & EXPERIENCE Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical ...

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All JobsData Scientist Machine Learning JobsTemporary Data Scientist Machine Learning JobsTemporary Data Scientist Machine Learning Jobs in Madison, WI

Temporary Data Scientist Machine Learning information

See Madison, WI salary details

$37.8K

$123.7K

$198K

How much do temporary data scientist machine learning jobs pay per year?

As of Sep 15, 2026, the average yearly pay for temporary data scientist machine learning in Madison, WI is $123,675.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,300.00 and $137,000.00 per year, depending on experience, location, and employer.

What does a temporary data scientist specializing in machine learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a temporary data scientist specializing in machine learning?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary data scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.

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

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Madison, WI?

The most popular types of Data Scientist Machine Learning jobs in Madison, WI are:

What are popular job titles related to Temporary Data Scientist Machine Learning jobs in Madison, WI?

For Temporary Data Scientist Machine Learning jobs in Madison, WI, the most frequently searched job titles are:

What job categories do people searching Temporary Data Scientist Machine Learning jobs in Madison, WI look for?

The top searched job categories for Temporary Data Scientist Machine Learning jobs in Madison, WI are:

Infographic showing various Temporary Data Scientist Machine Learning job openings in Madison, WI as of June 2026, with employment types broken down into 18% Full Time, 71% Part Time, 2% Temporary, and 9% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $123,675 per year, or $59.5 per hour.

Machine Learning Engineer

Whitewater, WI

Bespoke Labs
See more jobs at Bespoke Labsexternal

Full-time

Re-posted 3 hours ago

Job description

  • Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch

  • Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration

  • Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues

  • Build evaluation harnesses and benchmark infrastructure, with held-out sets and contamination controls, so results are trustworthy

  • Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams

  • Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics

  • Implement methods from recent ML papers quickly and turn them into production-grade systems

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