Lead Data Scientist

Comcast; Leeds; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading video streaming service in the UK seeks a Lead Data Scientist to develop recommendation and personalization solutions. In this role, you will collaborate with a cross-functional team to enhance personalization models, working on cutting-edge machine learning methods. The ideal candidate should possess a Master's or PhD in a relevant field and have over 5 years of experience in machine learning, including application in the content streaming industry.

Qualifications

• 5+ years of combined experience in machine learning in industry or research.
• Experience with commercial recommender systems or advanced research projects.
• Strong experience with deep learning using TensorFlow.

Responsibilities

• Develop recommendation and personalization models using statistical and machine learning methods.
• Collaborate with software and data architects to build automated implementations.
• Drive innovation in statistical and machine learning methodologies.

Skills

Machine learning

Data Science

Python

Statistical analysis

Deep learning

Collaboration

Education

Master or PhD in Statistics, Computer Science, Data Science or relevant field

Tools

Google Cloud Platform

TensorFlow

SQL

PySpark

Kubeflow

Airflow

Job description

Overview

As part of the Peacock Data Science team, the Lead Data Scientist will be responsible for creating recommendation and personalization solutions for one or more verticals of Peacock Video Streaming Service. You'll collaborate with an international, cross‑functional team of engineers, architects, product managers and analysts to identify and prioritize enhancements to Peacock’s personalization models. Your responsibilities will touch everything from feature creation to model evaluation and deployment, and you’ll have opportunities to work on cutting‑edge machine learning like foundation models and reinforcement learning.

Responsibilities

• Work with a group of data scientists in the development of recommendation and personalization models using statistical, machine learning and data mining methodologies.
• Drive the collection and manipulation of new data and the refinement of existing data sources.
• Translate complex problems and solutions to all levels of the organization.
• Collaborate with software and data architects in building real‑time and automated batch implementations of data science solutions and integrating them into the streaming service architecture.
• Drive innovation of the statistical and machine learning methodologies and tools used by the team.

Qualifications

• Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Machine Learning, Mathematics, Operations Research or another quantitative field or equivalent.
• 5+ years of combined experience in machine learning in industry or research.
• Experience with commercial recommender systems or a lead role in an advanced research recommender system project.
• Working experience with deep learning and graph methodologies in machine learning. Strong experience with deep learning using TensorFlow.
• Experience implementing scalable, distributed, and highly available systems using Google Cloud Platform.
• Experience with Google AI Platform/Vertex AI, Kubeflow and Airflow.
• Proficient in Python. Java or Scala is a plus.
• Experience in data processing using SQL and PySpark.
• Experience working with foundation models and other GenAI technologies.
• Experience in media analytics and application of data science to the content streaming and TV industry.
• Good understanding of reinforcement learning algorithms.
• Experience with multi‑billion record datasets and leading projects that span the disciplines of data science and data engineering.
• Experience with large‑scale video assets.
• Team oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools.