Director, Data Science - Personalization & Product Analytics

Univision

Education
Benefits
Skills

ABOUT THE ROLE & TEAM:

TelevisaUnivision is the leading Spanish-language media company in the world! We’re investing in our content, our people, and our properties, which span digital, streaming, social, audio, linear and live events. We’re growing our offerings, building on the launch of our successful streaming platform ViX.

TelevisaUnivision is seeking a Director of Data Science, Personalization and Product Analytics to join our Enterprise Data Science team. The Enterprise Data Science team serves as the data science hub for the organization, providing access and insights to our business leaders as they both develop new services and optimize existing services. This team is responsible for building and enhancing large-scale and high-performance systems to organize and store data from multiple platforms and conducting advanced statistical analyses to help optimize the experience for our digital audience. This team also develops key data assets for the company, including the TelevisaUnivision Household Graph, personalization and lifecycle propensity algorithms for ViX, lookalike modeling capabilities, proprietary customer segments, and manages relationships with key partners to improve UCI data assets and enable new data-driven services.

The Director of Data Science, Personalization and Product Analytics will be responsible for leading and developing the team driving personalization and advanced analytics efforts for ViX, the largest Spanish-language streaming platform in the world. This individual will guide development of the recommendation engine that powers many experiences on the ViX app, lifecycle propensity models that score users based on different behaviors (churn/upgrade/resubscription likelihood), and advanced analyses of ViX consumers as they traverse the ViX app, leveraging assets including the household graph and other proprietary data products to arrive at defensible, data-driven recommendations for product improvement. You are expected to be a player-coach, with an equal amount of time spent on hands-on technical work and mentoring junior colleagues. This role reports into the Head of Data Science.

YOUR DAY-TO-DAY: (Responsibilities)

  • Manage, grow, and motivate a team of data scientists
  • Be a technical leader and go-to expert for tactics and technical strategy for all things personalization
  • Maintain and improve the recommendation engine powering ViX, our direct-to-consumer streaming platform
  • Maintain, improve, and increase the usage of lifecycle propensity models leveraged by the ViX product and marketing teams
  • Own the buildout, maintenance, and enhancements around our customer profile
  • Execute deep-dive analyses that are priorities for the ViX operations organization
  • Facilitate data-driven and informed decision making and prioritization
  • Develop strong cross-functional partnerships across ViX and the broader TelevisaUnivision organization to drive team success
  • Drive outstanding performance for the Personalization and Product Analytics pod

YOU HAVE:

  • 3+ years of experience with team leadership or team management
  • 6+ years of experience with data science
  • Experience building customer-facing personalization/recommendation solutions in a prior role
  • Demonstrated use and understanding of statistical analysis
  • Expert level proficiency in Python
  • Expert level proficiency in SQL
  • Expert level proficiency with at least one cloud architecture service (GCP/AWS/Azure)
  • Bachelor’s degree in a broadly quantitative field
  • Experience conducting analyses to drive business impact
  • Experience communicating effectively with business leaders and cross-functional stakeholders of different disciplines
  • Experience managing multiple projects and deadlines in a fast-paced environment with minimal guidance

YOU HAVE:

  • Experience building and deploying recommendation engines for a D2C ((preferably video streaming) app
  • Experience doing deep product analytics work for a D2C (preferably video streaming) app
  • Extensive experience with Google Cloud Platform, leveraging Vertex AI and Google BigTable
  • Advanced (M.S./Ph.D.) degree in a broadly quantitative field
  • Experience with large data sets and data warehouse environments (Big Query/Snowflake)
  • Ability to thrive in a high pressure and rapidly changing, less structured environment
  • Ability to multi-task, meet deadlines, and maintain focus and confidentiality
  • Strong relationship building ability
  • Excellent written and verbal communication skills
  • Full professional proficiency in English and either professional Spanish proficiency or the desire to become proficient in Spanish
  • Has knowledge of and actively consumes TelevisaUnivision content is a plus!

ELIGIBILITY REQUIREMENTS

  • Must be willing to work in the US
  • Employment/education will be verified
  • Applicants must be currently authorized to work in the United States on a full-time basis

Exact compensation may vary based on skills, experience, and location. Please note the national salary range listed in the job posting reflects the new hire salary range across levels and U.S. locations that would be applicable to the position.

Salary Range:

170,000 - 215,000 + benefits

OUR BENEFITS:

TelevisaUnivision believes that a happy, well-balanced employee is what makes our culture thrive. We offer a wide selection of perks and benefits including PTO; tuition reimbursement; wellness and employee support programs; 401K; and life and other insurance plans. This is all in addition to our

comprehensive and competitive health benefits package featuring medical, dental and vision coverage options.

Univision is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.

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Confirmed 2 hours ago. Posted 30+ days ago.

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