Director, AI/ML & Data Science

• 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.

Job Description

Job Summary

• The Director of AI/ML & Data Science Gracenote India will be central to the success of the data
• science teams across geographies. This role is fundamental to the growth and success of
• Gracenote AI & Data Science organization as a whole. Key goals of this role are to establish the
• technical rigor, culture and operating rhythm of the organization, delivering the business outcomes
• for Gracenote and working with local and global stakeholders to collaborate on key outcomes and
• deliverables. This role will involve leading initiatives in AI, core data science, NLP, computer vision
• and MLOps.

Responsibilities

• ● Manage multiple teams of Gracenote data science and analytics engineers, with direct and
• indirect managerial responsibilities.
• ● Work with local and global management across all relevant org partners to ensure success
• and productivity and business outcomes of assigned teams.
• ● Create a culture based on Nielsen values, fostering a culture of collaboration, innovation, and
• continuous learning and growth.
• ● Establish operating rhythm and cadence within areas of responsibility to ensure transparent
• communication and inclusiveness, with the aim of creating a positive high retention
• environment for associates.
• ● Track KPIs including productivity and employee retention.
• ● Coordinate and maintain a talent pipeline, including connections with Universities and
• supporting internships and new joiner programs.
• ● Continuously assess and improve business processes.
• ● Apply an automation mindset to automate processes for recurring analyses and simulations,
• focusing on efficiency.
• ● Oversee the deployment and maintenance of machine learning models, AI & LLM based
• solutions and data pipelines in a production environment.
• ● Establish and enforce rigorous quality assurance processes to maintain the integrity and
• accuracy of audience measurement data.
• ● Ensure adherence to tools of the Product Development Lifecycle.
• ● Drive research initiatives to improve existing methodologies for statistical sampling and
• research for panels and surveys.
• ● Oversee evolution of analytics to incorporate more predictive and prescriptive analytics into
• Nielsen’s operational processes.
• ● Identify and implement market research methodologies appropriate for the media
• measurement space.
• ● Represent Global Data Solutions Data Science and Analytics team in cross-functional (e.g.,
• Product, Technology, Audience Measurement Data Science) engagements.
• ● Stay abreast of emerging trends, technologies, and best practices in data science, market
• research, and media analytics, contributing to thought leadership initiatives and industry
• forums.
• ● Lead initiatives in core data science, including statistical modeling, machine learning, data
• mining, and experimental design.
• ● Develop and implement NLP solutions for text analysis, sentiment analysis, topic modeling,
• information extraction, and chatbot development.
• ● Lead computer vision projects, including image/video analysis, object detection, image
• classification, facial recognition, and video understanding.
• ● Utilize GenAI tools for workflow creation, including building and deploying Agentic RAG
• systems, Small Language Models (SLMs), text generation, and content summarization.

Qualifications

• ● Bachelor’s/Master’s degree or PhD. (preferred) in a quantitative research field, such as
• computer science, data science, statistics, mathematics, biological/physical sciences, etc.
• ● 10+ years of experience working with Data Science, AI, deep learning and statistics.
• ● Proven track record in team building.
• ● 8-10 years of experience with statistical coding languages such as Python, Spark, SAS, R,
• Scala, and/or SQL.
• ● 3-5 years of experience working in a cloud-based environment, ideally AWS.
• ● Good understanding of business tools such as JIRA, Airflow, Confluence, Smartsheets,
• Google Workspace suite.
• ● Excellent statistical and analytical skills.
• ● Experience in data integrations (e.g., developing data pipelines, analytics workflows,
• self-service apps)
• ● 3-5 years experience with low-code/no-code tools (e.g., Alteryx).
• ● 3-5 years experience in visualization tools e.g., Tableau, PowerBI, Looker, Spotfire,
• Salesforce dashboards.
• ● Excellent communication (verbal and written) and presentation skills in English.
• ● Excellent critical thinking and problem-solving skills.
• ● Sense of curiosity, skepticism, and attention to detail.
• ● Knowledge of market research methodologies, media consumption trends, and media
• industry regulations is a plus.
• ● Strong foundation in core data science principles, including statistical modeling, machine
• learning algorithms, and data manipulation techniques.
• ● Experience with NLP libraries and frameworks (e.g., NLTK, SpaCy, Hugging Face
• Transformers, Gensim).
• ● Experience with computer vision libraries and frameworks (e.g., OpenCV, TensorFlow,
• PyTorch, Keras).
• ● Hands-on experience with GenAI tools and techniques, including RAG, SLMs, prompt
• engineering, and fine-tuning pre-trained models.
• ● Familiarity with deploying and managing machine learning and GenAI models in production
• environments.

Additional Information

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