iSpot
DataScienceIntern
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Science Intern at iSpot. Skills: Data science, Machine learning, Statistical modeling. Conduct data analysis. Build statistical models”
Industry & Context.
Solve complex challenges
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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