GenAi Manager - Data Science - Marketing

About the Role

We are looking for a seasoned AI professional with 11–12 years of experience in Data Science, Machine Learning, and Applied AI to lead the development of AI-powered marketing solutions. This role will partner with Marketing, Demand Generation, Sales, and Revenue teams to build scalable AI and Generative AI capabilities that improve campaign performance, personalization, customer engagement, lead conversion, and revenue growth.The ideal candidate combines strong ML fundamentals with 2–4 years of hands-on experience building enterprise Generative AI solutions and has successfully partnered with Marketing or Growth teams to deliver measurable business impact.

Key Responsibilities

• Define and drive the AI roadmap for Marketing, Demand Generation, and Revenue functions.
• Build ML models for audience segmentation, campaign optimization, personalization, lead scoring, forecasting, and marketing analytics.
• Design and deploy enterprise GenAI solutions using LLMs (OpenAI, Gemini, Claude, etc.) for content generation, AI assistants, sales enablement, and customer engagement.
• Develop RAG-based applications and AI agents leveraging enterprise knowledge and marketing content.
• Build scalable AI pipelines integrating CRM, marketing automation, web analytics, and other business data sources.
• Ensure production readiness through model deployment, monitoring, AI observability, and data governance.
• Partner with cross-functional teams to identify AI opportunities, deliver business value, and drive adoption.
• Mentor technical teams and stay current with emerging AI technologies and best practices.

• 11–12 years of experience in Data Science, Machine Learning, AI Engineering, or Applied AI.
• 2–4 years of hands-on experience building production-grade Generative AI applications.
• Experience working closely with Marketing, Demand Generation, Growth, or Revenue Operations teams.
• Proven track record of delivering AI solutions that drive measurable business outcomes.
• Strong expertise in Machine Learning, NLP, predictive modeling, recommendation systems, and marketing analytics.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, embeddings, and vector databases.
• Strong proficiency in Python and SQL, with experience integrating AI models into production environments.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps tools such as MLflow, Airflow, Databricks, or similar.

• Experience with Salesforce, HubSpot, Marketo, Adobe Experience Cloud, Google Analytics, or similar MarTech platforms.
• Experience in B2B SaaS, Enterprise Technology, or Consulting environments.
• Strong stakeholder management and leadership skills with the ability to influence business and technical teams.