Engagement Manager (Tech, Media and Telecom)

Overview

Fractal is seeking an Engagement Manager – Decision Science to join their Bay Area, CA team. This role involves helping leading technology organizations achieve measurable outcomes through cutting-edge GenAI, Data Science, Engineering, and Behavioral Science capabilities.

Responsibilities

• Serve as the primary point of contact for senior client stakeholders as strategic partners.
• Lead delivery of complex analytics and AI-driven programs, ensuring quality and timely outcomes.
• Proactively innovate solutions leveraging decision science, behavioral insights, and emerging AI capabilities.
• Foster collaboration across multi-disciplinary teams and drive delivery excellence.
• Identify opportunities to deepen client relationships and expand engagement scope.
• Contribute to thought leadership and practice growth initiatives.

Qualifications (Must Have)

• 10-14 years of experience in analytics consulting or decision science leadership roles.
• Proven ability to manage senior client relationships and 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)

• 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.
• Exposure to standard ML techniques (e.g. regression, clustering, experimentation, forecasting).
• Interest in emerging GenAI applications and trends.