Machine Learning Intern

About the Role

The Data Science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the internship, functional and demonstrable progress has been made in a way that can be integrated into the functional portfolio of the team.

Important: the data science internship does not necessarily transition to a full-time role at the end of the period. Depending on team need, firm budget, and fit, interns should not expect their time to conclude with an offer.

Example Projects

• Anomaly detection using deep neural networks
• Numerical optimization applied to problems in manufacturing
• Personal identifiable information (PII) and personal health information (PHI) detection in natural language

Areas of Focus

The data science internship is intended to expose the intern to what it means to do data science on a team in an enterprise setting. Interns should expect to engage with the following components:

Modeling

• Understanding how to frame business problems as data science problems
• Navigating the full data science lifecycle: research and exploration, development, deployment, support
• Using correct model selection and training procedures to prevent common modeling errors
• Creating reasonable test scenarios and diagnostic measures

Software Development

• Writing high-quality Python (readable, reusable, modular, and well-abstracted code)
• Using Linux, the terminal, and other core development tools
• Understanding source control (git), containerization (docker), and deployment technologies (CI/CD, Kubernetes)
• Participating in code reviews

Business Value and Processes

• Contributing to team development processes and agile/scrum rituals
• Helping to clarify and prioritize work, define success criteria, and own work item completion
• Applying all relevant change management controls for risk and compliance policies
• Presenting work clearly to technical and non-technical audiences

Qualifications

Relevant majors and areas of expertise:

• Data Science
• Computer Science
• Mathematics
• Natural or Social Sciences

Relevant additional backgrounds also considered.

Responsibilities

• Anomaly detection using deep neural networks
• Numerical optimization applied to problems in manufacturing
• Personal identifiable information (PII) and personal health information (PHI) detection in natural language
• Understanding how to frame business problems as data science problems
• Navigating the full data science lifecycle: research and exploration, development, deployment, support
• Using correct model selection and training procedures to prevent common modeling errors
• Creating reasonable test scenarios and diagnostic measures
• Writing high-quality Python (readable, reusable, modular, and well-abstracted code)
• Using Linux, the terminal, and other core development tools
• Understanding source control (git), containerization (docker), and deployment technologies (CI/CD, Kubernetes)
• Participating in code reviews
• Contributing to team development processes and agile/scrum rituals
• Helping to clarify and prioritize work, define success criteria, and own work item completion
• Applying all relevant change management controls for risk and compliance policies
• Presenting work clearly to technical and non-technical audiences
• Upholding Crowe’s values of Care, Trust, Courage, and Stewardship
• Acting ethically and with integrity at all times

Pay

A reasonable estimate of the current range is $27.00 - $42.00 per hour.

Benefits

Crowe offers employees a comprehensive total rewards package, including:

• Exceptional people experience in an inclusive culture that values diversity
• Consistent career coaching and guidance from a dedicated Career Coach
• Opportunities for career growth and leadership development