Senior Analyst, Marketing Analytics
Santa Monica, CA
Hulu's Data team is seeking a Manager, Data Product Management who will be an exceptional addition to our growing product team. This roll will lead and strengthen a team of skilled data product managers, responsible for delivering data products and solutions for Hulu's needs. The ideal candidate is an experienced data product and career manager, capable of building skilled and engaged teams, having handled several multi-year product roadmaps simultaneously. Candidate is capable of constructing and executing sophisticated, interlocking product solutions, and have demonstrated proficiencies in working both inside and outside the organization to deliver results for viewers, partners, and internal teams. This candidate builds fantastic relationships across all levels of the organization and is recognized as a problem solver who looks to elevate the work of everyone around them. If you love data and creating products and capabilities to redefine data and how it is utilized, this is a phenomenal role!
WHAT YOU'LL DO
• Define the vision, strategy, and roadmap for data products and capabilities aligned to organizational and business goals
• Build relationships with key technology and business teams to ensure success
• Partner with Analytics, Data Science, Data Engineering, Data Architecture, Data Quality & Governance, Product Design, and other Technical Program Management team members to develop, test, and deliver high quality products and features
• Lead and drive teams on all business readiness activities, including product planning, sequencing, testing, user education, rollout, iteration, and support
• Develop detailed product requirements, user stories, acceptance criteria, and success measures
• Ability to identify risks, resolve key blockers, and establish appropriate resolution paths
• Ability to fill in gaps across roles and functions as needed, performing as an adaptive problem solver
• Ability to champion a collaborative work environment that cultivates shared understanding, transparency, autonomy, innovation, and continuous learning
WHAT TO BRING
• Minimum of 3+ years in product management experience with building and delivering successful data products, services and capabilities
• Knowledge and experience with marketing technologies and systems is critical. (Salesforce, GA, multi-touch attribution, segmentation, campaign management, etc.)
• Planning acumen and proven ability to break down work and define an MVP, as well as subsequent iterations
• Highly analytical and collaborative qualities with strong technical, strategic and problem-solving skills
• Experience and comfort solving problems in an ambiguous environment where there is constant change. Have the tenacity to thrive in a dynamic and fast-paced environment, inspire change, and collaborate with a variety of individuals and organizational partners
• Experience utilizing both qualitative analysis and quantitative analysis techniques and familiarity with common data science models and approaches to problem-solving. Generally: the ability to plan for what analysts and data scientists need to deliver.
• Experience demonstrating leadership, self-motivation, accountability, and a standout colleague.
• Managing large scale implementation of data sets including - data ingestion, integration and reporting tools experience.
• Understanding of the Data science workflow, the terminology and the unique challenges associated with the domain
• Undergraduate Degree in Engineering, Math, Science, Economics, or equivalent.
• Advance CS degree or MBA is a plus
• Knowledge and experience with marketing technologies and systems (Salesforce, GA, multi-touch attribution, segmentation, campaign management, etc.)
• Shown experience in video streaming and OTT
• Experience with ThoughtSpot, Tableau or other visualization tools
• Experience with large scale enterprise applications using big data open-source solutions such as Hadoop, HBase, Spark, Kafka, and Elastic Search / Solr
• Experience or knowledge of basic programming and DB's technologies (SQL, Python, Cassandra, MongoDB, Redis, Couchbase, Oracle, MySQL, Teradata)