Data Science/ML Intern (open to UG and high school students)

Key Skills

Effective communication skills, Machine learning techniques, Pandas, Python Programming, Scikit-learn, Tableau

Job Description

One of our awesome industry partner companies, Elemental Cognition, is looking for a full-time (40 hours/week) 10-week intern. Position is open to undergraduate and high-school students. Pay is $20-25 per hour, commensurate with experience.

Company 

Elemental Cognition (“EC) is building the future of AI by changing the way machines learn, understand, and reason. Led by Dr. David Ferrucci, the creator of IBM Watson and well-known AI luminary, Elemental Cognition is a research-driven company delivering revolutionary products that solve challenging, real-world problems.

EC’s ultimate goal is to develop collaborative AI that will be capable of building and sharing deep understanding, ultimately producing richer, more effective machine-to-human interactions. This AI won’t only provide answers but will explain what it is thinking and why, enabling the human user to make more informed decisions. And, crucially, it will also learn as it helps solve problems. From democratizing knowledge to turning computers into powerful thought partners, the potential for business, and the world at large, is almost endless. 

Our team of scientists and engineers has built an impressive array of AI technology components that are already being assembled into several compelling commercial product offerings.

What You’ll Do

The data science/ML intern will work across a variety of data science and machine learning projects, supporting research staff members.

Key Responsibilities

• Label and annotate user data
• Write scripts for data analysis
• Create metrics for data analytics
• Bug fixes
• Ad hoc tasks to support team members

Requirements

• Education in computer science or related technical fields.
• Coding languages: Must have 1+ years of coding in Python; Javascript and SQL are helpful but not required.
• Familiarity with machine learning concepts, models, libraries.
• Knowledge of data structures and algorithms.
• Familiar with expectations and etiquette of working in a professional environment (e.g.,

respectful of deadlines, appropriate communication over Slack, etc).

• Some experience with version control (Git)