At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.
Roles and Responsibilities:
Lead the design, development, and implementation of AI/ML-based solutions across various product lines.
Collaborate with product managers, data engineers, and architects to translate business requirements into data science problems and solutions.
Take ownership of end-to-end AI/ML modules, from data processing to model development, testing, and deployment.
Provide technical leadership to a team of data scientists, ensuring high-quality outputs and adherence to best practices.
Conduct cutting-edge research and capability building across the latest Machine Learning, Deep Learning, and AI technologies.
Prepare technical documentation, including high-level and low-level design, requirement specifications, and white papers.
Evaluate and fine-tune models, ensuring they meet performance requirements and deliver insights that drive product improvements.
Production exposure to Large Language Models (LLM) and experience in implementing and optimizing LLM-based solutions.
Must-have Skills:
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4-6 years of experience in Data Science and AI/ML product development, with a proven track record of leading technical teams.
Expertise in machine learning algorithms, Deep Learning models, Natural Language Processing, and Anomaly Detection.
Strong understanding of model lifecycle management, including model building, evaluation, and optimization.
Hands-on experience with Python and proficiency with frameworks like TensorFlow, Keras, PyTorch, etc.
Solid understanding of SQL, NoSQL databases, and data modeling with ElasticSearch experience.
Ability to manage multiple projects simultaneously in a fast-paced, agile environment.
Excellent problem-solving skills and communication abilities, particularly in documenting and presenting technical concepts.
Familiarity with Big Data frameworks such as Spark, Storm, Databricks, and Kafka.
Experience with container technologies like Docker and orchestration tools like Kubernetes, ECS, or EKS
Optional (Good To Have) Skills:
Experience with cloud-based machine learning platforms like AWS, Azure, or Google Cloud.
Experience with tools like MLFlow, KubeFlow, or similar for model tracking and orchestration.
Exposure to NoSQL databases such as MongoDB, Cassandra, Redis, and Cosmos DB, and familiarity with indexing mechanisms.
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