At Hulu, the number one priority is our customers. We make business decisions around our customers’ preferences. The Data Science team at Hulu combines deep data analysis and research of our rich user data to better understand the needs of our subscribers and make optimal decisions about our product experience and the content we create or acquire. We are looking for a seasoned leader to lead a team of talented data scientists who employ a diverse ecosystem of innovative machine learning models to enable rapid product experimentation and higher ROI content decisions. A successful leader in this space will be a strong executor, as well as a technical expert. The Director will interact closely with business stakeholders to understand their needs, communicate vision and roadmap, give updates on progress, and most importantly ensure delivery of relevant solutions for the business. You will work on a variety of domains such as data science, machine learning, inference and optimization; you will not only lead our cutting edge analytical solution development pipeline and ensure it provides maximal value, but also grow a team culture of research, innovation, and contribution.
Set a vision and strategy that is focused on customer value, owning the overall analytic output of Hulu’s Data Science teams
Recruit and grow a talented team of Data Scientists and Data Science Managers
Partner in analytical roadmap development with Strategic and Functional Analytics teams, to address the needs of Content Acquisition, Product Management, Finance, Marketing (Acquisition and Retention), Advertising, Tech, and other internal stakeholders
Act as part research leader and part engineering leader to drive execution
Interface with key Tech teams to integrate data collection, data quality and core model output into production systems
Integrate deeply with VP and C-level business leadership as a trusted and influential contributor to data-driven decision making, ensuring maximum impact of Data Science outputs
Advise on model selection and questions of accuracy vs immediacy
Guide and evangelize development of projects and technologies that accelerate iterative, rapid experimentation processes including feature engineering and data sharing across analytics teams
Support and showcase a long-term research agenda aimed at generating innovations to solve critical business needs and technical challenges
Evolve agile/iterative development process to drive timely Data Science outcomes and reinforce the test-and-learn culture
Present our learnings and output at conferences, and engage the team in external activities that help elevate Hulu’s Data Science brand
Create opportunities for collaboration with other data science and research teams in other business units and Hulu offices in other cities
WHAT TO BRING
PhD/MS in computer science, machine learning, statistics, applied mathematics, physics, or other scientific or computational disciplines
Expertise developing algorithms for advanced analytics and experimental measurement, using machine learning and statistics, coupled with software engineering for both prototype and production systems
Exceptional leadership skills and experience in building and maintaining a high performing, customer-focused, and fun team-culture
An inclusive and hands-on servant-leadership and collaborative style aimed at developing and motivating a team of data scientists
Skill at building relationships across the organization and becoming a trusted, sought-after partner
Strong coaching skills and long-term career guidance for managers
Talent in analytical storytelling with exceptional ability to convey complex analytical results to business stakeholders in relevant and accessible language
A strong passion and evangelism for data science, coupled with deep desire to adapt machine learning technologies to enable extremely effective solutions to Hulu's most challenging data analysis problems
8+ years’ experience building, managing, mentoring, and inspiring teams, with a proven track record of leveraging data to drive business results
Strong background working with large-scale data in distributed computing environments, including databases, data cleaning, and feature engineering
Experience with Agile/iterative process in the context of research and analytics
Relentless focus on execution with demonstrated ability to get things done
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