Headline

Project Manager | Turning user pain points into scalable, data-backed product decisions | PSPO-I Certified | AI in Agile Project Management | IIM Kashipur MBA

About

Most project/products don’t fail because of a lack of talent. They fail in the void — the space between what a business asks for, what a designer envisions, and what an engineer can actually build. That’s where I operate. I work at the intersection of product, delivery, and systems — connecting dots across disciplines to turn ambiguity into execution. Along the way, I’ve: • Built 0→1 platforms and delivery frameworks that scale across teams and use cases • Audited the invisible — broken processes, cost leakages, and hidden risks • Translated across teams, aligning business intent, design thinking, and engineering reality • Stepped beyond defined roles because real ownership isn’t constrained by titles I don’t see teams as functions. I see them as orchestras. Different strengths, different rhythms but when there’s trust, alignment, and clarity, execution becomes seamless. That’s the environment I build. Because in high-ambiguity spaces — especially AI and 0→1 systems — trust isn’t a soft skill. It’s infrastructure. I believe the best products come from the space between disciplines: where PMs think like designers, designers think like users, and no one waits for permission to care. — If you’re building AI products, scaling delivery, or navigating complex systems — let’s connect.

Location

Kolkata

Work experience

Associate Project Manager - II at PalTech, May 2025 - Present · 1 yr 2 mos, Currently working as an offshore project manager for a US-based AI/LLM and data analytics services firm operating in regulated sectors — healthcare, legal, and finance. Responsible for cross-project visibility and delivery accountability across multiple simultaneous client engagements. Focus areas include establishing delivery processes and governance structures, managing vendor transitions, tracking deliverables across diverse end-client portfolios, and identifying and mitigating operational inefficiencies/risks before they become business problems. Exposure spans medical writing, media monitoring and analysis, and AI-assisted workflows within highly regulated environments where accuracy, compliance, and traceability are non-negotiable.

Associate Project Manager - I at PalTech, May 2024 - Apr 2025 · 1 yr, Worked as an embedded project manager on a 0-to-1 ATS product build in the HR tech domain — spanning the full delivery lifecycle from requirements and design to sprint management and production releases. Beyond delivery, contributed to organisational capability building: redesigned engineering onboarding, built governance frameworks, and established a centralised knowledge infrastructure used by 200+ people across delivery teams. Developed hands-on depth across business analysis, UX inputs, stakeholder management, agile ceremonies, release coordination, and people management — often wearing multiple hats within the same sprint cycle.

Product Manager Intern at Talent Litmus, Apr 2023 - Jun 2023 · 3 mos, Mumbai, Maharashtra, India, First exposure to a product-first environment in the HR tech space — specifically the AI-interviewing and talent assessment domain. Worked across competitive research, user journey analysis, MVP scoping, and internal workflow automation. Gained early experience translating messy, multi-source inputs — user research, demo feedback, competitor patterns — into structured product thinking that influenced real roadmap decisions.

Executive Administrator at Maa Durga Plastic, Jul 2020 - Jun 2022 · 2 yrs, West Bengal, India, Early career role that built foundational instincts around operations, process design, and data-driven decision making — in a manufacturing and supply chain context. Worked across inventory planning, logistics, production workflow redesign, and quality management. Learned how broken processes compound quietly — and how fixing them upstream prevents larger downstream losses. That instinct has followed every role since.

Research Intern at IIIT Hyderabad, Jun 2019 - Nov 2019 · 6 mos, Hyderabad, Telangana, India, Research exposure in natural language processing and machine translation during undergrad — working on pipeline optimisation and model training efficiency. Introduced early to the gap between academic AI and production-ready systems, and the unglamorous data work that bridges them.

Education

Master of Business Administration - MBA, Analytics, Indian Institute of Management Kashipur

Bachelor of Technology - BTech, Computer Science and Engineering, Banasthali Vidyapith