Pranay Rawat

Consultant

New York, New York, United States3 yrs 5 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Proven track record in driving user growth.
Expertise in product management and operations.
Strong analytical skills with a focus on consumer behavior.

Stackforce AI infers this person is a Product Management and Operations expert in the Retail and SaaS industries.

Contact

pranayrawat95@gmail.com LinkedIn

Skills

Core Skills

Product ManagementProduct OperationsCommunity ManagementMarketingNatural Language Processing (nlp)Machine Learning

Other Skills

Agile MethodologiesAmazon Web Services (AWS)Anomaly DetectionArtificial Intelligence (AI)Attention MechanismsCompetitive AnalysisData AnalysisDeep LearningFigma (Software)Front-End DevelopmentGenerative AIGraph TheoryGrowth StrategiesHadoopJava

About

After working for two years at Amazon, the world's largest E-commerce company, I developed a deep interest in the retail and consumer products sector. My time at Amazon, renowned for its customer-centric approach, highlighted the transformative impact of technology on the retail sector and provided me with valuable insights into consumer behavior. Fascinated by this I decided to continue my higher education. Currently, I am pursuing a Master’s in Management Science and Engineering at Columbia University, New York. My studies focus on strategic and analytical frameworks, with a particular emphasis on their application to the retail and consumer product industry. I am actively seeking summer internships for 2025 in consulting or product management roles in the domain, where I can leverage my background and academic knowledge to drive meaningful contributions.

Experience

Bill & melinda gates foundation

Strategy Consultant

Sep 2024 – Present · 1 yr 6 mos · United States · Remote

1. Built financial models for 7 global regions; regression analysis on 10,000+ data points pinpointed profitability drivers (CPM, CTR, bounce rate).
2. Enhanced ad spend ROI by 13% through value-based pricing strategies and revealed 3 untapped monetization channels.
3. Synthesized complex analyses into clear recommendations, influencing leadership’s strategic roadmap.

Kering

Strategy Consultant

Sep 2024 – Present · 1 yr 6 mos · United States

1. Benchmarked best practices across e-commerce, consumer goods, and luxury retail, exposing capability gaps in logistics and supply chain.
2. Synthesized insights from 10+ executive interviews into an actionable upskilling roadmap, guiding Kering leadership’s supply chain capability-building and transformation strategy.

Columbia university

Graduate Assistant

Aug 2024 – Dec 2024 · 4 mos · New York, United States · On-site

Assisted Prof. Anthony Effik in teaching Digital Operating Strategies course.

Fotomateai

Product & Strategy Lead

Apr 2023 – Dec 2023 · 8 mos

1. Spearheaded go-to-market strategy, forging 10+ SaaS partnerships and unlocking $2M in revenue potential.
2. Transformed market research into actionable insights by synthesizing 30+ data sources, driving sharper customer segmentation and competitive positioning.
3. Elevated customer retention by reducing API latency by 15ms and cutting churn 10% MoM through cross-functional product improvements.

WireframingProject ManagementGenerative AIProduct OperationsFigma (Software)Product Road Mapping+2

Syfe

Product Operations Associate

May 2022 – Jul 2022 · 2 mos · Singapore · Remote

1. Boosted funnel conversion by 6% MoM by diagnosing drop-offs and implementing deep link integration.
2. Increased service efficiency by 17% by leading development of AI-driven query segmentation tool, reducing customer response times and costs.

Product Operations

Amazon

Software / Product

Jul 2021 – Mar 2023 · 1 yr 8 mos

1. Delivered 7–8% monthly active user growth and accelerated partner onboarding by 15% through SQL-driven funnel analysis and targeted feature launches.
2. Automated device onboarding workflows via ETL pipelines and AWS Step Functions, cutting deployment time by 85% and freeing 200+ engineering hours quarterly, equivalent to ~$65k in labor expense reduction.
3. Reduced device time-to-market by 9% through workflow logic enhancements, directly impacting product rollout speed.
4. Designed and A/B-tested ‘App Health Insights’ dashboard, earning leadership approval for company-wide rollout with an estimated $12M annual revenue impact.

React.jsProject ManagementAmazon Web Services (AWS)MVP developmentProduct Lifecycle ManagementSoftware Design+8

Delhi technological university (formerly dce)

Research Fellow

Sep 2020 – Mar 2021 · 6 mos · Delhi, India

Worked in the domain natural Language Processing domain to solve one of the most popular topics of abstractive summarization. Here we proposed a multi-document summarizer that works best on non-static data, where data keeps on changing, like summarizing movie reviews which keep on increasing in magnitude.

Natural Language UnderstandingSequence modellingSoftware DevelopmentGraph TheoryAttention MechanismsNatural Language Processing (NLP)

All india ai/ml masters community (aimc)

Founding Member

Jun 2020 – Jul 2021 · 1 yr 1 mo

Founded and led a core team of 12 students to establish the first AI/ML society at Delhi Technological University.
Successfully Expanded the community to become the largest on campus, boasting over 400 members within six months.
Conducted live classes, expert webinars, and socializing events for better community engagement.

Project ManagementMedia OutreachArtificial Intelligence (AI)MarketingGrowth StrategiesCommunity Management+2

Globallogic

Data Scientist

Dec 2019 – Feb 2020 · 2 mos · Noida, Uttar Pradesh

Worked with various financial services clients to draw insights from the vast amount of user/company data.
Utilized unsupervised clustering algorithms like DBSCAN on ~2M customer data points to achieve a 93% recall rate in detecting anomalies. A fintech client utilized this model to detect potential loan defaulters
Used predictive model markup language to devise and document a method to store large machine-learning models in a platform-independent format. The team could use it to run models created for vanilla python environments in Spark, Hadoop, etc.

Anomaly DetectionPredictive ModelingPython (Programming Language)KerasHadoopMachine Learning+1