iSpot
ResearchDataScientist
Neural analysis suggests this role is
optimal for Entry candidates.
“Research Data Scientist at iSpot. Skills: Data Analysis, Modeling, Machine Learning Model Development, Data Pipeline Development, Research and Innovation. Conduct in-depth data analysis and build advanced statistical models to extract insights from large viewing and demographic datasets.. Develop, train, and deploy state-of-the-art machine learning models to solve a variety of measurement problems.”
What You'll Achieve.
contribute to the success of something great; key contributor to the future growth of the company; scale our models to satisfy the needs of brands, publishers, networks, and agencies
Industry & Context.
critical thinking; solve complex challenges
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.
What They're Looking For.
Must Have
Degree in mathematics, economics, statistics, computer science, physics, social sciences, or other quantitative discipline., 1-3 years of professional experience in data science and/or modeling, Technical understanding of machine learning, statistics, data science, and related fields, Advanced user in several quantitative software tools, particularly Python, R, and/or willingness to learn new tools as needed, Expert at wrangling data and conducting thorough data analyses, Experience working with high dimensional data sets
Nice to Have
A master's degree is preferred but not required., Pragmatic, team-oriented; builds rapport and respect communication, writing, and critical thinking attention to detail
What You'll Do.
Conduct in-depth data analysis and build advanced statistical models to extract insights from large viewing and demographic datasets.
and deploy state-of-the-art machine learning models to solve a variety of measurement problems.
Work with our Engineering teams to design and implement efficient data pipelines to collect
and transform data from various sources.
Stay up-to-date with the latest data science techniques
and explore novel approaches to solve complex challenges.
How You'll Work.
Team & Collaboration
work with our product and engineering teams to scale our models; team-oriented
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 Scientist is a key contributor to the future growth of the company, pushing 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, and creative testing. 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. 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: Degree in mathematics, economics, statistics, computer science, physics, social sciences, or other quantitative discipline. A master's degree is preferred but not required. 1-3 years of professi
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