Senior/Lead Data Scientist

At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future. 
Senior/Lead Data Scientist will work on new technology and research projects within the content recognition and classification area of Nielsen. You will be working to identify and/or classify content from both audio and video. In order to make these technologies, you should have a good theoretical background and practical experience with machine learning systems. Theoretical knowledge about audio or video is required, and you should be capable of performing signal processing on either audio or video data. We expect you to be well versed in engineering best practices and software design concepts, and to be able to document and explain your work. You will coordinate your work with the tasks of colleagues from your own team and other Nielsen teams.
You will interact with Nielsen customers and partners as required while developing the next content recognition or classification product. As time allows, you will advise and lead other engineering colleagues and student interns. You could also initiate or participate in the publication of scientific papers, and represent Nielsen at scientific Conferences.

REQUIREMENTS:

• Bachelor’s degree in Computer Science and/or Electrical Engineering and at least 5+ years  of practical experience in multimedia signal processing and programming. Masters or PhD in Computer Science, Electrical Engineering, or a related field is preferred.
• Solid fundamentals (practical and theoretical) in machine learning and digitalsignal processing of either audio or video.  Must be proficient in multiple modeling techniques including neural networks.
• Experience with accelerated machine learning tools such as Tensorflow, Keras,PyTorch, etc.
• Experience developing end to end project workflow in machine learning systems. This includes literature review, data collection, building ML system infrastructure, evaluation systems, and production/integration into a final service.
• Good programming skills in Python and C/C++. Good knowledge of debugging techniques and applications development.
• Knowledge of audio or video fingerprinting.
• Experience handling large amounts of data and familiarity with databases. Bash and shell scripting experience.
• Very good knowledge of Linux/Unix platforms and Windows or Mac OS.
• Knowledge about visual perception, and/or audio and music theory.
• Experience with cloud services such as AWS or Google Cloud.
• Quickly understand and properly judge the applicability of scientific publications and technical papers.