Location: New York NY - San Francisco CA - Santa Monica CA
We are seeking a Manager to lead a team of engineers focused on harnessing engineering datapoints via innovative analysis, data science approaches and engineering processes. This role will partner closely across engineering verticals and executive leadership to design and deploy production engineering processes and data science models to drive data scoring, quality and engineering insights.
Disney Media & Entertainment Distribution (DMED) brings together the Company's best-in-class product, technology, and commercialization teams together into one global organization. DMED is responsible for the P&L management and all distribution, network and engineering operations, sales, advertising, data, and certain key technology functions worldwide for the Company's content engines. DMED also manages operations of the Company's streaming services including Disney+, Hulu, ESPN+ and Disney+ Hotstar; and domestic broadcast and cable television networks.
• Manage a team of engineers responsible for performing data analysis and data science applications via production engineering processes to inform engineering intelligence on the health of our services, clients, products and offerings - Rapidly prototype, build and deploy production level models to monitor critical datasets in streaming and batch
• Adapt methods from diverse disciplines such as machine learning, deep learning, artificial intelligence, statistical modelling, information theory, information retrieval and other areas to gain data insights, draw conclusions and work with business partners to put those insights into action
• Own and contribute to engineering solutioning of complex model scoring, quality scoring and model deployment, including roadmapping with an emphasis on ensuring high quality engineering processes and scalability across all practices
• Lead engineering datapoint quantification as part of the engineering teams continuous delivery and deployment lifecycle via device testing and automation partnering across QA engineering teams
• Lead support to escalate and triage data quality issues across the engineering organizations, outlining path to remediation and raising required dependent engineering work
• Develop a deep understanding of our engineering infrastructure and systems that support our customer facing products.
• Serve as a source of knowledge and delegator for junior engineering data scientists and analysts performing peer code reviews and auditing of production level models and functions
• Create and manage key engineering health KPIs through regular monitoring in a scalable way as systems and products expand
• 3-5 years' experience in a data science or engineering function leading data scientists, data analysts, quality assurance analysts, quantitative scoring, or similar discipline diligently applying principles, practices, and theory for backlog and project management
• 2+ years of experience managing a team
• 2+ years of Python, Spark, Pyspark or Scala is required
• Strong sense of ownership over deliverables, as this role will have end-to-end responsibilities for certain production engineering processes
• High familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Redshift, Airflow
• Good skills and knowledge of leadership, facilitation, situational awareness, conflict resolution, continual improvement, empowerment, and increasing transparency.
• Excellent written and verbal communication skills. Able to communicate anywhere from the team level to C-level executives.
• Minimum two years of experience in the technology industry, knowledge of streaming datasets a plus.
• BA or BS in a quantitative field (Business, Math/Statistics, Economics, CS, Engineering, or similar) is desired
Jobcode: Reference SBJ-d9359k-3-236-117-38-42 in your application.