Director, AI/ML & Data Science

Company Description

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

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.