Srissti Tyagi
Pernod Ricard India | SPJIMR, PGDM 2021-23 | Times Internet | Info Edge | B.Tech, Computer Science
- Role
- Digital Product - Manager at Pernod Ricard India
- Location
- Gurugram, IN
- LinkedIn followers
- 500 followers
About Srissti Tyagi
With over four years of experience in technology, I bring a strategic mindset, analytical rigor, and a passion for building user-centric, scalable solutions. My MBA from SPJIMR has sharpened my business acumen, leadership, and management skills, while my B.Tech in Computer Science equips me with a strong technical foundation to collaborate effectively with engineering teams. I thrive on transforming complex challenges into innovative, automated solutions that enhance user experiences and create meaningful impact. Skilled in roadmap planning, stakeholder alignment, and data-driven decision-making, I excel at executing go-to-market strategies that drive product adoption and business growth. With a proactive and results-driven approach, I ensure continuous improvement, optimizing products to stay ahead in a dynamic, competitive landscape. I’m deeply motivated by the intersection of technology and human experience, always seeking to leverage cutting-edge solutions to simplify everyday interactions and deliver lasting value.
Experience
Digital Product - Manager
Jun 2023 — Present · Gurugram, IN
Driving digital product initiatives across sales, marketing, and operations. Partnering cross-functionally to deliver scalable platforms and process automation aligned with business goals.• Led rollout of a digital sales enablement platform, collaborating across design, commercial, and data teams to enhance workflows and drive early adoption.• Supported product planning and user research efforts, improving feature discoverability and accelerating go-to-market through iterative delivery.• Strengthened data governance by aligning digital processes with compliance standards and internal SOPs, reducing turnaround times and risks.• Managed vendor-led deployment of sensor-based infrastructure to enable AI-powered predictive maintenance; coordinated delivery across machines and aligned outcomes with operational KPIs and strategic planning.
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