Company:
Cint
Location: New York County
Closing Date: 17/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Job Description
Role Overview
As a Principal Data Scientist at Cint, you will lead advanced analytics and data science initiatives for Data Solutions and Media Measurement product lines. This role involves using statistical modeling, machine learning, large language models and advanced data analysis techniques. Ultimately, you will be accountable for developing and maintaining research methods that align Cint capabilities with market claims and industry standards of measurement. The ideal candidate will possess strong technical and thought leadership skills and will be comfortable working cross-functionally with product, engineers, and business stakeholders.
Key Responsibilities:
Develop and deploy statistical models, machine learning algorithms, and custom analytics solutions to measure the effectiveness of media campaigns.
Collaborates with cross-functional teams to design, refine and automate measurement methodologies for TV, digital, social, and other media platforms.
Lead the research and discovery phases for both new and existing products and partner closely with engineering teams to transition prototypes into robust, scalable solutions.
Develop customer-facing methodology resources and thought leadership. Support business teams in explaining and defending our measurement methodologies broadly to customers.
Independently plan, develop, and manage projects from concept to completion with no supervision, ensuring timely and high-quality delivery.
Partner with product teams and other stakeholders to translate business needs into actionable data science initiatives.
Serve as a technical leader and mentor to other data scientists in the team, promoting best practices in coding, experimentation, and analytical techniques.
Stay updated with the latest industry trends and emerging methodologies in media measurement and data science.
Communicate complex results, insights and strategic recommendation to non-technical audiences through compelling data visualizations, detailed reports and presentations
Role Overview
As a Principal Data Scientist at Cint, you will lead advanced analytics and data science initiatives for Data Solutions and Media Measurement product lines. This role involves using statistical modeling, machine learning, large language models and advanced data analysis techniques. Ultimately, you will be accountable for developing and maintaining research methods that align Cint capabilities with market claims and industry standards of measurement. The ideal candidate will possess strong technical and thought leadership skills and will be comfortable working cross-functionally with product, engineers, and business stakeholders.
Key Responsibilities:
Develop and deploy statistical models, machine learning algorithms, and custom analytics solutions to measure the effectiveness of media campaigns.
Collaborates with cross-functional teams to design, refine and automate measurement methodologies for TV, digital, social, and other media platforms.
Lead the research and discovery phases for both new and existing products and partner closely with engineering teams to transition prototypes into robust, scalable solutions.
Develop customer-facing methodology resources and thought leadership. Support business teams in explaining and defending our measurement methodologies broadly to customers.
Independently plan, develop, and manage projects from concept to completion with no supervision, ensuring timely and high-quality delivery.
Partner with product teams and other stakeholders to translate business needs into actionable data science initiatives.
Serve as a technical leader and mentor to other data scientists in the team, promoting best practices in coding, experimentation, and analytical techniques.
Stay updated with the latest industry trends and emerging methodologies in media measurement and data science.
Communicate complex results, insights and strategic recommendation to non-technical audiences through compelling data visualizations, detailed reports and presentations
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