Engagement Manager (TMT)

Key Responsibilities

• Serve as the lead for India based team and interface with senior delivery leaders as well as clients.
• Lead delivery of complex analytics and AI-driven programs, ensuring quality and timely outcomes.
• Build and groom high performing teams with effective hiring processes, onboarding systems and proactive, targeted interventions.
• Proactively innovate solutions leveraging decision science, data science, behavioral insights, engineering and Gen AI capabilities.
• Foster collaboration across multi-disciplinary teams and drive delivery excellence by identifying process improvement opportunities.
• Continuously keep abreast of Tech industry developments to consult clients and proactively innovate on their behalf.
• Contribute to thought leadership and practice growth initiatives by preparing case studies, publishing articles and attending industry conferences.

Core Requirements (Must Have)

• 8-14 years of experience in analytics consulting or decision science leadership roles.
• Proven ability to lead teams and work with US based counterparts and managing senior client relationships to deliver complex programs.
• Strong problem-solving mindset with first-principles thinking.
• Established subject matter expert in 1 or more of the following – data science, digital marketing, behavior science, GenAI, product management, software development with strong familiarity or interest in remaining fields.
• Excellent communication and team leadership skills; ability to mentor and build high-performing teams.
• Culture fit: Humble, Hungry, Smart (HHS) with a collaborative approach.

Preferred Skills (Good To Have)

• Familiarity with SQL and Python for problem-solving (hands-on).
• Exposure to consulting frameworks e.g. 5-whys, issue tree, prioritization matrix.
• Exposure to project management frameworks e.g. agile, waterfall, scrum.
• Exposure to product management concepts e.g. PRD, backlog grooming, user stories.
• Experience in digital analytics, experimentation, and data-driven decision-making.
• Understanding of Adobe Analytics concepts and digital data structures.
• Experience with standard ML techniques (e.g. regression, clustering, experimentation, forecasting).
• Interest in emerging GenAI applications and trends.