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Machine Learning Winter Internship Jobs in Utah (NOW HIRING)

Brex Rotational Program

Salt Lake City, UT ยท On-site

$58K - $66K/yr

... machine learning, or data analysis. * Leadership roles in university clubs or organizations related to data science, AI, computer science, or business analytics. * Prior internships/full-time roles ...

This temporary internship runs through the end of October and provides hands-on experience with ... Comfortable learning new software and technologies. * Basic computer proficiency, including ...

Mechanical Engineering Intern

Draper, UT ยท On-site

$20 - $40/hr

The ideal candidate enjoys learning independently, takes pride in finding practical solutions, and ... Basic machining or fabrication experience What Makes This Internship Different Unlike many ...

Mechanical Engineering Intern

Draper, UT ยท On-site

$20 - $40/hr

The ideal candidate enjoys learning independently, takes pride in finding practical solutions, and ... Basic machining or fabrication experience What Makes This Internship Different Unlike many ...

Since 2012, we've used data, machine learning, and a more human approach to create flexible ... Internship experience in analytics, finance, technology, or related industries. * Curiosity for ...

This role is ideal for an engineer who enjoys solving problems, working collaboratively, learning ... Equivalent internship, co-op, laboratory, manufacturing, or machining experience is highly ...

This role is ideal for an engineer who enjoys solving problems, working collaboratively, learning ... Equivalent internship, co-op, laboratory, manufacturing, or machining experience is highly ...

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Machine Learning Winter Internship information

What types of projects and tasks can I expect to work on during a Machine Learning Winter Internship?

During a Machine Learning Winter Internship, you can expect to work on hands-on projects such as data preprocessing, building and evaluating machine learning models, and assisting with research experiments. Interns often contribute to real-world applications, such as developing predictive analytics tools, optimizing algorithms, or supporting deployment efforts. Collaboration is common, as you'll work closely with data scientists, engineers, and sometimes product teams, giving you exposure to the full machine learning workflow. This environment provides an excellent opportunity to apply theoretical knowledge, gain practical experience, and build a professional network in the field.

What is a Machine Learning Winter Internship?

A Machine Learning Winter Internship is a short-term, practical training program typically offered during the winter months for students or early-career professionals interested in machine learning. Interns work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced mentors. The internship provides hands-on experience with tools and techniques used in the field, helping participants build technical skills and gain industry exposure. These positions are often offered by tech companies, research labs, or startups and can be either remote or onsite. Successful completion of a machine learning internship can enhance a candidate's resume and open up further career opportunities in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as a Machine Learning Winter Intern, and why are they important?

To thrive as a Machine Learning Winter Intern, you generally need a solid foundation in mathematics, programming (especially Python), and a basic understanding of machine learning concepts, often acquired through coursework or relevant projects. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries like Pandas and NumPy is typically required. Strong problem-solving abilities, collaboration, and curiosity help interns stand out in team-based, fast-paced environments. These skills are crucial for effectively contributing to real-world projects and quickly learning from experienced professionals during the internship.

What is the difference between Machine Learning Winter Internship vs Data Science Winter Internship?

AspectMachine Learning Winter InternshipData Science Winter Internship
Required CredentialsUndergraduate or graduate in CS, AI, or related fields; some knowledge of ML frameworksUndergraduate or graduate in Statistics, Math, CS; familiarity with data analysis tools
Work EnvironmentResearch labs, tech companies, startups focusing on ML modelsData analysis, visualization, and interpretation in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, consulting

While both internships involve working with data, the Machine Learning Winter Internship emphasizes developing and applying ML algorithms, whereas the Data Science Winter Internship focuses on analyzing data, creating reports, and deriving insights. Candidates should choose based on their specific skills and career goals in AI or data analysis.

What cities in Utah are hiring for Machine Learning Winter Internship jobs? Cities in Utah with the most Machine Learning Winter Internship job openings:

Senior Data Analyst - Fraud Strategy & Operations

Raisin

Lehi, UT โ€ข Hybrid

$80K - $101K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 23 days ago


Job description

Team

The Risk and Fraud Operations team plays a central role in safeguarding Raisin's business by monitoring, assessing, and mitigating risks across all operational areas. We are responsible for managing fraud prevention, detection and mitigation, investigations and recoveries, monitoring for financial crime events (AML, KYC) and implementing effective risk controls to support the company's growth. Our work bridges business, compliance, and technology-analyzing data, processes, and transactions to identify potential threats while also enabling smooth and secure customer experiences.
We collaborate closely with cross-functional teams (Product, Compliance, Customer Service, and Engineering) to design and execute risk and fraud management frameworks, enhance operational efficiency, and maintain a strong culture of accountability.
Your Responsibilities
As the Senior Data Analyst - Fraud Strategy & Operations, you will be the driving force behind our fraud defense system. We are looking for a proven analytical mind from the financial services sector who can challenge our current thinking, build predictive fraud models, redesign existing fraud models, framework and processes. Using SQL, Python/R Ecosystems, Feature Engineering, you will dissect fraud trends, build predictive models from scratch, and implement sharp, real-time rules to prevent and detect fraud across our payment rails.ย 
This role reports to the Head of Risk and Fraud Operations and requires a highly capable and entrepreneurial individual who can balance deep technical hands-on execution with high-level strategy.

  • Advanced Fraud Strategy & Analytics
    - Uncover Trends: Conduct complex data analysis using SQL, Python and Feature Engineering to proactively identify emerging fraud patterns and system vulnerabilities before they impact the platform.
    - Deploy Fraud Rules: Design, test, and implement robust fraud prevention rules that successfully catch bad actors while maintaining a seamless experience for real customers.
    - Drive Strategy: Elevate Raisin US's capabilities by introducing industry best practices, new methodologies, and innovative fraud prevention strategies that we aren't using today.
    - KPIs & Dashboards: Build out data-driven dashboards to track fraud metrics, losses, and mitigation performance, presenting actionable findings directly to leadership.
  • Model Development & Maintenance
    - Build Predictive Models: Design, build, and deploy machine learning and predictive models utilizing Python to detect anomalies across the entire customer journey (onboarding, funding, and money movement).
    - Feature Engineering: Develop model features based on identity, device, behavioral, and transactional data.
    - Cross-Functional Delivery: Partner closely with Product and Engineering to integrate these models into our real-time production pipelines.
  • AML & Financial Crime Collaboration
    - Risk Profiling: Partner with the Compliance team to enhance customer risk profiling, transaction monitoring, and KYC/AML workflows.
    - Design low-friction, custom risk rules for identity verification, account takeover protection, and transaction monitoring.
    - Continuous Back-Testing: Routinely stress-test current rules against changing regulatory standards and evolving financial crime tactics.

Your Profile

  • Financial Services Background: 8+ years of experience in fraud risk management, analytics, or financial crime specifically within fintech, retail banking, or digital payments.
  • Master of Analytics: Exceptional analytical capabilities are your biggest asset. You love diving into raw data to solve complex puzzles.
  • Technical Stack: Highly proficient in SQL and Python for data manipulation, analytics, and building predictive models. Experience building out fraud dashboards is a must.
  • Payment System Domain Expertise: Deep understanding of Deposits and ACH is required; direct experience with modern instant payment systems like RTP and FedNow is highly preferred.
  • Rule & Model Builder: Proven track record of designing custom fraud rules and deploying machine learning or statistical models in a live environment.

Join our mission, join our team - and grow with us!

At Raisin, we care about each other and it is one of our top priorities to foster an open and caring environment in which everyone feels welcome and comfortable. Our culture is strongly driven by our ambitious team, which connects more than 75 different nationalities.

As part of our team, you will benefit from:

  • Flexible working hours and up to 28 days PTO accrued from your first month, plus 13 public holidays.
  • Employee Development Budget of $2,200 and 4 full training days per year.
  • Company 401k contribution of 5%.
  • Healthcare coverage contribution, including medical, dental and vision.
  • Commuter benefits and flexible working from home policy.
  • Regular team events and yearly Summer and Winter Party.