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Internship Applied Scientist Machine Learning Jobs in Illinois

Gotion, Inc.

Machine Learning Engineer

Manteno, IL

S. in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field * Demonstrated expertise in model development, optimization, and algorithmic ...

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

S. in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field * Demonstrated expertise in model development, optimization, and algorithmic ...

IMC Trading

Machine Learning Researcher

Chicago, IL · On-site

The role involves designing and deploying machine learning models, collaborating with trading teams ... Science, or related quantitative field • 2+ years of experience building applied ML models • ...

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All JobsApplied Scientist Machine Learning JobsInternship Applied Scientist Machine Learning JobsInternship Applied Scientist Machine Learning Jobs in Illinois

Internship Applied Scientist Machine Learning information

What types of projects do internship applied scientists in machine learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an internship applied scientist in machine learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an internship applied scientist in machine learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.

What are the most commonly searched types of Applied Scientist Machine Learning jobs in Illinois?

The most popular types of Applied Scientist Machine Learning jobs in Illinois are:

What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Illinois?

For Internship Applied Scientist Machine Learning jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Internship Applied Scientist Machine Learning jobs in Illinois look for?

The top searched job categories for Internship Applied Scientist Machine Learning jobs in Illinois are:

What cities in Illinois are hiring for Internship Applied Scientist Machine Learning jobs?

Cities in Illinois with the most Internship Applied Scientist Machine Learning job openings:

Internship Applied Scientist Machine Learning jobs near you

Applied Scientist III - Shipper Pricing

Uber Freight

Chicago, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 29 days ago

Uber Freight rating

7.3

Company rating: 7.3 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

169th of 362 rated logistics

Job description

Schedule: Full Time Employment
Job Type: Hybrid
Salary Type: Salary
Req #:2538
About the Role
As an Applied Scientist III on the Shipper Pricing team, you will apply machine learning, casual inference and optimization techniques to develop and improve Uber Freight's algorithms for real time bidding on shipper freight. You will have a direct impact on Uber Freight's key business metrics and work closely with senior ICs to shape the technical direction for this area. You will collaborate closely with Product, Operations, Engineering, and other scientists in the department on a daily basis.
What the Candidate Will Do
  • Develop creative algorithms for optimally trading off gross revenue and net revenue when bidding on shipper freight in real time across a variety of settings, e.g., open auctions, sealed auctions, reverse waterfall auctions, etc.
  • Prototype and evaluate solutions using statistical analysis and simulation.
  • Collaborate with engineering teams to deploy, experimentally evaluate, and productionize these solutions.
  • Leverage data to understand product performance and identify improvement opportunities, including analyzing potential causal factors.
  • Establish standard methodologies for data science, including modeling, coding, analytics, and experimentation.
  • Communicate findings and insights to senior management and cross-functional teams.
  • Provide recommendations to assist quick product ideation and feature launch decisions.

Basic Qualifications
  • M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background
  • 3+ years of experience in developing and deploying machine learning models and optimization algorithms in production environments
  • Proficiency in designing, launching, and analyzing A/B tests or other types of online experiments
  • Expertise in observational causal inference or statistical analysis
  • Proficiency in Python, SQL and Spark

Preferred Qualifications
  • Experience developing NN algorithms
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Track record of translating ambiguous business problems into technical solutions
  • Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners
  • Familiarity with reinforcement learning and causal machine learning

Benefits & Compensation for U.S. Employees
Employees working more than 30 hours in the US at Uber Freight are eligible for benefits like a company sponsored health plan, dental and vision benefits, 401k match, financial and mental wellness benefits, parental leave, short- and long-term disability coverage, life insurance and more. US based employees may also be eligible for a performance or sales incentive bonus program, participation in Uber Freight equity awards, and other types of compensation depending upon the role.
About Uber Freight
Uber Freight helps companies move goods more reliably and efficiently. We bring together the technology, people, and transportation capacity they need, using real-time data from millions of shipments to guide smarter decisions. That helps customers spot issues early, avoid costly surprises, and deliver on time. Uber Freight works with 1 in 3 Fortune 500 shippers across North America and manages over $17B in freight. Learn more at www.uberfreight.com.
Candidate Privacy Notice
Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice.
EEOC
Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
For Chicago-based roles: The salary range for this role is $124,600.00 - $151,950.00 per year

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