Senior Data Scientist

Paramount•New York, NY

15d

About The Position

We are seeking a Senior Data Scientist who is excited to build ML products that shape business strategy, optimize content, inform marketing investment decisions, and enhance the user experience. You will leverage rich datasets such as video and ads consumption, clickstream activity, subscription history, and 2nd/3rd party data to build user- and session-level causal and predictive models. Key applications include identifying the drivers of retention, quantifying the impact of high-value user actions, forecasting content viewership, developing user segmentations for cohort-based targeting, and surfacing opportunities to enhance the user experience. Success in this role requires a strong foundation in Python and SQL, comfort writing production-quality code in a collaborative environment, effective communication skills, and a willingness to continuously learn new tools and techniques.

Requirements

2+ years experience in Data Science and ML Engineering.
MS or Ph.D in Statistics/Data Science/Computer Science or related disciplines with specialization in machine learning techniques.
Experience with both supervised and unsupervised learning methodologies.
Full stack experience in data collection, aggregation, analysis, visualization, productionalization, and monitoring of data science products.
Familiarity with well-known statistical and ML models and methods.
Ability to innovate without over-engineering.
Communicate concisely and persuasively with a wide variety of stakeholders.
Strong detail orientation with a penchant for data accuracy.
Must successfully pass a background check.

Nice To Haves

Experience using Google Cloud Platform (BigQuery, ML Engine, and APIs).
Experience with integrating AI solutions into existing business processes.
Experience using project management tools like those from Atlassian (JIRA, Confluence)

Responsibilities

Translate complex business problems into coherent, actionable quantitative solutions.
Implement, automate, and maintain reliable, performant, and end-to-end ML systems using software engineering and MLOps best practices.
Deliver clear, impactful insights to stakeholders through effective communication.
Collaborate with stakeholders across the Product org to operationalize data science solutions that inform strategy and optimize the user experience.
Promote best practices across the data science and product analytics team.