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Full Time Job

Sr Lead Data Scientist

Peacock

New York, NY 01-13-2021
 
  • Paid
  • Full Time
  • Senior (5-10 years) Experience
Job Description

Responsibilities
Meet Peacock, NBCUniversal's new, wildly entertaining streaming service that combines timeless shows and movies with timely news, sports and pop-culture.

We're growing our team of smart, hungry, and upbeat doers who crave the chance to build something new at the epicenter of content, tech, and culture. We need fearless leaders and pop-culture fiends who work hard and fan hard. Creative problem-solvers who just so happen to be the reigning champs at Parks & Rec trivia night. So if this sounds like you, join our flock. And we promise, we won't put your stapler in Jell-O.

As part of the Direct-to-Consumer Decision Sciences team, the Lead Data Scientist will be responsible for creating analytical solutions for one or more verticals of NBCU's video streaming service including, but not limited to, the recommender system, automated marketing, personalized advertisement, commerce and revenue optimization systems, customer journey and CRM solutions.

In this role, the Lead Data Scientist will use advanced data science methodologies including collaborative filtering, deep learning, reinforcement learning, on-line modeling etc. and work closely with business owners, teammates and engineers to build a state-of-the-art real-time video streaming service.

Responsibilities include, but are not limited to:
• Lead a group of data scientists & engineers in the development of analytical models using statistical, machine learning and data mining methodologies. Advise, help to resolve issues and handle non-standard cases.
• Define procedures for cleansing, discretization, imputation, selection, generalization etc. to create high quality features for the modelling process.
• Work with business stakeholders to define business requirements including KPI and acceptance criteria.
• Use big data, relational and non-relational data sources to access data at the appropriate level of granularity for the needs of specific analytical projects. Maintains up to date knowledge of the relevant data set structures and participate in defining necessary upgrades and modifications.
• Collaborate with software and data architects in building real-time and automated batch implementations of the data science solutions and integrating them into the streaming service architecture.
• Drive work on improving the codebase and machine learning lifecycle infrastructure.

Qualifications/Requirements
• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent.
• 5+ years of combined experience in advanced analytics in industry or research.
• Experience in leading small teams or/and being a lead data scientist on large commercial projects.
• Deep knowledge of statistical methods and machine learning with special emphasis on the advanced algorithms like neural networks, SVM, random forests, bagging, gradient boosting machines, k-means++, deep learning or reinforcement learning. Advanced level in time-series and forecasting.
• Experience implementing scalable, distributed, and highly available systems using Google Cloud.
• Experience with data visualization tools and techniques.
• Proficient in at least one statistical (R, Python, etc.) languages.
• Strong skills in data processing using SQL and PySpark.

Desired Characteristics
• Experience with commercial recommender systems and/or content streaming services.
• Working experience with deep learning, particularly in the areas different form the computer vision.
• Experience with multi-billion record datasets and leading projects that span the disciplines of data science and data engineering
• Knowledge of enterprise-level digital analytics platforms (e.g. Adobe Analytics, Google Analytics, etc.)
• Experience with television ratings and digital measurement tools (Nielsen, Rentrak, ComScore etc.)
• Experience building streaming data pipelines using Kafka, Spark or Flink
• Experience with large-scale video assets
• Team oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools
• Pride and ownership in your work and confident representation of your team to other parts of NBCUniversal

Jobcode: Reference SBJ-g39v3x-18-216-123-120-42 in your application.