Data Scientist Intern

Working towards a degree or graduating in Computer Science, Statistics, Data Science, Electrical Engineering, or a similar field of study. Professional experience may be used in place of relevant education.
Demonstrate the ability to maintain a high level of integrity, discretion, and confidentiality of sensitive, complex information.
Have an eye for detail and have the ability to interpret data into simple, intuitive information.
Have a keen eye for the little things and are comfortable working in granular details. Organized and agile: You have excellent organization, prioritization, and time management skills.
Ability to work in a fast-paced environment to support a rapidly growing technology company.
Exceptional communication skills. Whether it is written or verbal, people know what you mean, what you are asking for, and what is expected.
Proficient in Python, SQL, MS Office (Word, Excel, and PowerPoint), and G Suite Programs (Google Docs, Google Sheets, Google Slides).
Familiarity with Python libraries such as NetworkX, Pandas, Numpy, and SkLearn.

Using Python & Pyspark to analyze large-scale data, research new features and models to classify fraudulent activity.
Build pipelines to process and aggregate data at scale to generate features for machine learning models.
Analysis of graph data to generate features, propagate knowledge, and classify characteristics of connectivity.
Presenting research findings to a large audience, from highly technical to business and customer-focused teams.
Building services to host machine learning models, including data parsing, feature generation, integration with requisite databases, and operational features.

Familiar with multiprocessing and multithreading in Python.
Have experience with large-scale graph data. Have deployed production code.
Familiar with common SaaS applications such as Okta, Google Workspace, Slack, etc.