Sr. Data Scientist, tvScientific
Technologies
Python · Scala · Apache Spark · Apache Beam · AWS Athena · statistics · machine learning · adtech · CTV
About Pinterest
Visual discovery and shopping platform that converts high-intent planning behavior into personalized recommendations, commerce journeys, and performance advertising for brands.
Public · 5000+ people
Job description
The full responsibilities and requirements are on the employer’s site.
Read the job description ↗Source and classification
Internal deployment & tooling · Evidence for this classification:
our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. About tvScientific tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business. As a key member of our Data Science team, you'll be responsible for turning data
More from the job description
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. About tvScientific tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combine [... source excerpt omitted ...] , digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business. As a key member of our Data Science team, you'll be responsible for turning data into actionable insights, driving business decisions, and owning analytics projects from inception to completion. Day to day, your role will involve developing customized reporting and analytics tools to meet the unique needs of our clients. What you'll do: Write production code in Python. Design, launch, and analyze experiments to optimize ad campaigns. Create reporting and analytics tools for the Data Science Team's customers. Translate insights from repor [... source excerpt omitted ...] of new reporting and analytics tools. Ability to quickly translate between DS Analytics & DS Product team. Strong track record of providing high-quality service to the DS team’s customers/stakeholders. Adtech or CTV experience. Bachelor’s degree in computer science, statistics, a related field or equivalent experience. Big data experience with Scala, Apache Spark, Apache Beam, and AWS Athena is a plus. Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review) High integrity and own
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