Principal Data Scientist - Media Measurement

4 days ago

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Cint

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Software services • Insight technology • Panel monetization • insights exchange platform • Research sample

1001 - 5000

💰 $13M Series B on 2010-09

Description

• As a Principal Data Scientist at Cint, lead advanced analytics and data science initiatives for Data Solutions and Media Measurement product lines. • Develop and deploy statistical models, machine learning algorithms, and custom analytics solutions to measure effectiveness of media campaigns. • Collaborate with cross-functional teams to design, refine and automate measurement methodologies for TV, digital, social, and other media platforms. • Lead research and discovery phases for both new and existing products and partner 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 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 stakeholders to translate business needs into actionable data science initiatives. • Serve as a technical leader and mentor to other data scientists, 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 recommendations through compelling data visualizations, detailed reports and presentations.

Requirements

• Advanced degree (Ph.D. or Master's) in a quantitative field such as Data Science, Statistics, Mathematics, Economics, or Computer Science with outstanding analytical expertise + 4 years focused on media measurement, marketing analytics, or advertising. • 10+ years of experience in data science, analytics, or related fields, with at least 4 years focused on media measurement, marketing analytics, or advertising. • Proven track record in leading large-scale data science projects, mentoring teams, driving strategy and delivering business impact. • Extensive experience in advanced statistical techniques and concepts e.g., multivariate (parametric/ non-parametric) testing, sampling theory, weighting/projection, experimental design, regression/predictive modeling, causal inference techniques. • Strong programming skills in Python (as statistical and ML package tools). • Proven expertise in advanced Python prototyping. • Proficiency with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and techniques (e.g., clustering, regression, decision-trees). • Advanced SQL skills and familiarity with big data technologies (Spark, Hadoop, Databricks). • Strong understanding of infrastructure cost management, particularly in relation to processing large datasets efficiently.