Nielsen
A global leader in media measurement, analytics and insights, Nielsen shapes the future of media with accurate measurement of what people listen to and watch worldwide.
- Open roles
- 139
- New role every
- ~0.7 days
- Posting trend
- 8.8× vs prior 90d
Job facts
- Location
- Bangalore, , India
- Type
- full-time
- Department
- Technology
- Posted
- Mar 05, 2026
More roles at Nielsen
- Sales Enablement Specialist II · Mumbai, , India
- Client Partner (Senior Account Executive I) · Seoul, , Korea, republic of
- Senior Manager, Strategic Finance · Remote, California, United States
- Director, Product Management · Remote, Remote, United States
- Vice President, Product Marketing · Remote, Remote, United States
- Lead, Digital Process Transformation · Mexico City, , Mexico
Director, AI/ML & Data Science
at Nielsen
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 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.
● 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.
Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.