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Associate Data Scientist Deep Learning Jobs in Milwaukee, WI

As a Data Scientist your work may be focused in a variety of areas, including Machine learning ... Experience in deep learning, predictive modeling, data mining, and time series analysis.

As a Data Scientist your work may be focused in a variety of areas, including Machine learning ... Experience in deep learning, predictive modeling, data mining, and time series analysis.

As a Data Scientist your work may be focused in a variety of areas, including Machine learning ... Experience in deep learning, predictive modeling, data mining, and time series analysis.

Develop and implement statistical and machine learning models * Fine-tune, optimize and ensure the ... Translate data science outputs into business outcomes and value delivered * Mentor and guide junior ...

Develop and implement statistical and machine learning models to solve business problems within a cross-functional team * Collaborate with senior data scientists to fine-tune, optimize and ensure the ...

... machine learning modeling experience. Prior experience must include: 4 years building and ... Current associates who require a workplace accommodation should refer to Fiserv's Disability ...

This role requires associates to be in-office 1 day per week, fostering collaboration and ... Apply machine learning and AI techniques to uncover leading indicators of health utilization trends ...

This role requires associates to be in-office 1 day per week, fostering collaboration and ... Apply machine learning and AI techniques to uncover leading indicators of health utilization trends ...

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Associate Data Scientist Deep Learning information

See Milwaukee, WI salary details

$56.7K

$67K

$127.1K

How much do associate data scientist deep learning jobs pay per year?

As of Jul 28, 2026, the average yearly pay for associate data scientist deep learning in Milwaukee, WI is $67,035.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,100.00 and $58,600.00 per year, depending on experience, location, and employer.

What is the difference between Associate Data Scientist Deep Learning vs Data Scientist?

AspectAssociate Data Scientist Deep LearningData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related; familiarity with deep learning frameworksBachelor's or Master's in CS, Statistics, or related; broader data analysis skills
Work EnvironmentFocus on developing deep learning models, often in AI or ML teamsBroader data analysis, visualization, and modeling across various projects
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, retail, tech, and more

The main difference is that Associate Data Scientist Deep Learning specializes in developing deep learning models, requiring specific knowledge of neural networks and frameworks. Data Scientists have a broader scope, including traditional data analysis, statistical modeling, and visualization. Both roles often require similar educational backgrounds but differ in technical focus and project types.

Data Scientist

Data Scientist

ATI

Cudahy, WI • On-site

Full-time

Posted 25 days ago


Job description

Proven to Perform.
From the edges of space to the bottoms of ocean, our materials are proven to perform -- and so is our team. We're hiring high performers as proven as our products. Join us.
ATI is seeking to hire a Data Scientist to support business unit-wide data analytics initiatives. This position will be based in Cudahy, WI.
As a Data Scientist your work may be focused in a variety of areas, including Machine learning predictions of material properties, thermal management of forgings, automated characterization methods, and design and improvement of manufacturing processes.
A successful Data Scientist will work cross-functionally across multiple levels, operate effectively in early-stage development of processes and procedures, and will possess a strong Continuous Improvement mindset.
Additional Responsibilities
  • Map data from multiple sources into new structures.
  • Work with business subject matter experts to determine best solutions
  • Serve as a subject matter expert in the capabilities of Data Science.
  • Collaborate with business owners to solve business problems using a broad spectrum of data science tools, packages and visualization techniques.
  • Build models and optimization tools to support large scale projects that utilize online, offline data, structured, and unstructured data.

Basic Qualifications
  • B.S. degree in computer science, engineering with a strong statistical and programming background.
  • Experience in deep learning, predictive modeling, data mining, and time series analysis.
  • Knowledge of image segmentation, generative models, convolutional neural networks.
  • Experience in applied machine learning.

Preferred Qualifications (in addition to Basic Qualifications)
  • Experience in PyTorch, Keras/Tensorflow.
  • Experience in explainable AI.
  • Experience in SQL data query, data cleaning
    • Experience in SAP Data Intelligence and/or Azure cloud computing a plus but not required.
  • If you have worked on PINN or used ML for solving materials science problem a big plus.

We thrive when the expectations are great, and the barriers are high. We're solving the world's most difficult challenges through materials science. Our advanced, integrated process technologies and proven performers give us a tremendous competitive advantage. When customers systems need to fly higher, dig deeper, stand stronger, and last longer -- anywhere on, above or below the earth -- ATI is proven to perform.
*It is ATI's policy to not provide immigration sponsorship for any of the company's positions.
ATI and its subsidiary companies will provide equal employment opportunities to all applicants without regard to applicant's race, color, religion, sex, gender, genetic information, national origin, age, veteran status, disability status, or any other status protected be federal or state law. The company will provide reasonable accommodations to allow an applicant to participate in the hiring process if so requested.