About the job
Join Philo: The Ultimate Streaming Experience for TV and Movie Enthusiasts
At Philo, our technology and product teams are on a mission to revolutionize television. We blend cutting-edge technology with the most captivating medium ever created to craft the TV experience we’ve always desired. Our approach involves utilizing cloud delivery, modern tech stacks, machine learning, and bespoke native app experiences across all platforms. We prioritize delivering a robust streaming experience while innovating future-ready multi-screen and multi-user playback solutions.
The Role of Data at Philo
Data is at the heart of Philo's operations. It informs our business decisions, enhances our streaming quality, drives product experiments to refine user journeys, and simplifies content discovery for our viewers. With over a billion streams annually, we harness an immense data reservoir that influences every facet of our organization. Our data platform operates on a grand scale, processing trillions of events each year through a petabyte-scale data lake, facilitating thousands of data workflows and analytical queries that guide our strategic direction.
We seek innovative individuals for our Data team who are eager to tackle diverse projects related to engagement, content discoverability, experimentation, acquisition, and retention within our streaming service. Collaborating closely with data scientists, analysts, and engineers, you will create and implement solutions directly for our platform. Your work will encompass foundational data platform tasks, including data warehouse architecture, metric governance, and ensuring semantic consistency throughout our data pipeline, as well as insights and modeling efforts that deliver tangible business value. Additionally, you will partner with stakeholders from various departments to understand business requirements, construct reliable data pipelines, and provide actionable insights that empower the entire team to excel.
We are driven by a passion for problem-solving and delivering data-driven insights across the company. Our work leverages both innovative techniques and established practices in collaboration with every department. We utilize modern open-source tools such as dbt, GrowthBook, Robyn, Superset, and PyTorch, alongside SaaS solutions like Segment, Redshift, Snowflake, SageMaker, AWS Glue, Mode, Omni, Avo, and BigEye.
Recent projects undertaken by our Data Science team include:

