iSpot

DataScienceIntern

$0k+ Bellevue, Washington, United States INTERNSHIP Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Science Intern at iSpot. Skills: Data science, Machine learning, Statistical modeling. Conduct data analysis. Build statistical models”

Industry & Context.

Problems you'll solve

Solve complex challenges

Eligibility Requirements

Authorized to work in the United States

What They're Looking For.

Must Have

Progress toward a degree in mathematics, economics, statistics, computer science, physics, social sciences, or other quantitative discipline

Nice to Have

Relevant work experience is preferred, PhD preferred

What You'll Do.

Conduct data analysis

Build statistical models

Develop machine learning models

Train machine learning models

Deploy machine learning models

Design data pipelines

Implement data pipelines

Research data science techniques

Explore novel approaches

How You'll Work.

Team & Collaboration

Engineering teams; Product teams

Communication Scope

Communication; Writing

Full Job Description

Immigration / Work Authorization Notice: Applicants must be currently authorized to work in the United States. iSpot is not able to sponsor or take over sponsorship of an employment visa for this position at this time. iSpot competes for the best talent. Our compensation packages consist of salary and equity in one of Seattle’s hottest start-ups, as well as other standard benefits. Most importantly, we provide a really interesting working experience, and the chance to contribute to the success of something great. What You’ll Be Part Of An iSpot Research Data Science Intern is a great opportunity to help iSpot push the boundaries on what is measurable in the TV viewing and advertising space. The Research Data Science team builds innovative solutions for iSpot’s audience measures, attribution and lift analytics, creative testing, and artificial intelligence implementations. After developing new methodologies and building prototypes, we work with our product and engineering teams to scale our models to satisfy the needs of brands, publishers, networks, and agencies in a constantly evolving marketing landscape. Potential Responsibilities: • Data Analysis and Modeling: Conduct in-depth data analysis and build advanced statistical models to extract insights from large viewing and demographic datasets. • Machine Learning Model Development: Develop, train, and deploy state-of-the-art machine learning models to solve a variety of measurement problems. • Data Pipeline Development: Work with our Engineering teams to design and implement efficient data pipelines to collect, process, and transform data from various sources. • Research and Innovation: Stay up-to-date with the latest data science techniques, tools, and technologies, and explore novel approaches to solve complex challenges. Qualifications and Education Requirements: ● Progress toward a degree in mathematics, economics, statistics, computer science, physics, social sciences, or other quantitative discipline. ● Relev

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