Twisa Pal

Product Manager

Bengaluru, Karnataka, India6 yrs 3 mos experience

Highly Stable

Key Highlights

Led product strategy for 120M+ MAU.
Designed personalized offers boosting customer retention.
Expert in data analysis and product management.

Stackforce AI infers this person is a Data-Driven Product Manager in E-commerce and Retail sectors.

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Skills

Core Skills

Product StrategyProduct ManagementData ScienceData Analysis

Other Skills

LeadershipTeam CoordinationCultural AwarenessCultural SensitivityCross-cultural Communication SkillsSQLRSix SigmaMicrosoft OfficeMicrosoft ExcelManagementMicrosoft WordPowerPointTeamworkProgramming

Experience

6 yrs 3 mos

Total Experience

3 yrs 2 mos

Average Tenure

Current Experience

Meesho

2 roles

Product Manager II (Applied ML/AI)

Promoted

Jan 2023 – Jul 2025 · 2 yrs 6 mos · Bangalore Urban, Karnataka, India

Setting up the Charter for Diversity and Exploration in Ranking and Recommendations. Previously, was the PM lead (1st PM) across all recommendation products for short term conversion. The 3 key problem statements were : closing the ongoing primary shopping intent (substitutes), closing an incomplete shopping intent (rediscovery), closing related secondary shopping intents (cross-selling); contributing to ~50% of platform orders
Own the product lifecycle end-end across the app from product strategy, design, development to experimentation, launch and maintenance. Drive decisions on what to show to which user and how - across both logic and discovery experience for 120M+ MAU

Data AnalysisLeadershipTeam CoordinationCultural AwarenessCultural SensitivityCross-cultural Communication Skills+2

Product Manager I (Applied ML/AI)

May 2021 – Dec 2022 · 1 yr 7 mos · Bangalore Urban, Karnataka, India

Target

3 roles

Data Scientist

Promoted

Feb 2020 – Apr 2021 · 1 yr 2 mos

Designed Personalised Offers for Loyalty Marketing (Retention & Reactivation), including creation of top performing offers for yearly mega sale events like Black Friday and Back to School.
Developed strategies for user targeting, offer type and offer depth design to move incremental revenue and reactivation of soon-to-churn users
Provided insights and recommendations to marketing and data science leadership
Owned data prep and performance measurement (including A/B experimentation and metrics creation)

Data AnalysisSQLRData Science