Data Science Intern

About Pinecone:

Pinecone is on a mission to build the search and database technology to power AI applications for the next decade and beyond. Our fully managed vector database makes it easy to add vector search to AI applications. Since creating the “vector database” category, demand has grown incredibly fast and it shows in our user base. We are a distributed team with clusters in New York, San Francisco, Tel-Aviv, and Manchester.

Pinecone is seeking a skilled and highly motivated data science intern to join our Data Engineering team in 2024. As part of the Data Engineering organization you will collaborate with cross-functional teams to develop and deliver conversion funnel metrics, cohort and segment analysis, and user and workload classifications to help understand our user base and how they use Pinecone to inform and evaluate Product development and launches.

In this role, you will:

• Partner with product, engineering and design to drive insights, identify opportunities, and understand user behavior and trends

• Thoroughly analyze and interpret data to identify patterns and generate insights.

• Define and monitor key metrics through tracking KPIs and dashboards

• Supervise model performance and find opportunities for improvement.

• Collaborate with multi-functional teams to translate insights into actionable solutions.

• Write clear and concise documentation of your work.

Required Qualifications & Skills:

• Working towards a Bachelors, Masters, or PhD degree in a technical field of study in Data Science, Engineering, Computer Science, Computer Engineering, Management Information Systems, or IT

• Enrolled in an accredited college/university with an anticipated graduation date in Winter 2024 or Spring 2025

• Strong data manipulation skills required including cleaning and handling data

• Programming proficiency in Python and SQL

• Experience with distributed computing framework

• Excellent communication and storytelling skills.  You like to share and communicate your findings through writing or visualizations.