Gosuddin Siddiqi
Gen AI, ML, NLP at Microsoft AI
- Role
- Senior Applied Scientist at Microsoft
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Gosuddin Siddiqi
An Applied Scientist at Microsoft. End to End scenario owner from idea inception to deployment for maximizing business value. Let\'s Talk!
Experience
Senior Applied Scientist
Mar 2021 — Present · Redmond, WA, US
Quality of News Feed Recommendations: • Founding Tech Lead of Video Content Quality signals orchestrating cross-functional strategy to all stakeholders. Achieved remarkable growth with +2.3% Cold Users,+2.46% No Action Users,+3.52% Video Ad Revenue per user,+9.51% Non Video Ad Revenue,+1.91% Time Spent on Video Verticals and +1.94% on Watch Page.• Led and Accomplished the Key Results of Ranking and Organizing the recommendable content catalog that establishes each Content Partner’s authority on a given topic resulting in +0.62% Partner Improvement,+1.19% Daily Active Users,+0.21% Positivity in News Feeds,+4.12% on Product Expectation • Devised LLM Prompts to curate the ground truth for 2 content quality problem statements of subjective nature that identifies and differentiates best recommendable content for First Run Experience • Redefine existing basic user cohorts by introducing a concept of varying degree of interaction to serve user relevant and appropriate level of Quality Content, delivering +9% gains in overall Quality of the content feed • Designed and Developed End-to-End, multitude of features to support and create existing Machine Learning models, resulting in cumulative gains on Daily Active Users of +1.21%, 4.54% Content Interaction gains and +1.5% Revenue gains • Led the foundation of Analytics platform for measuring Content Quality and measuring effects on User Base, such as defining User Cohorts, Retention Rates and Methods, affinity towards good and poor-quality Content. Defined Interaction based Metrics as User Acceptance Rate and Content Exposure Rate to synergize User-Content Interaction signals • Patented “Two Stages of Local Recommendation” enabled location-based recommendations that improved User Location Document Understanding Location distance from 100+ kms to <10 kms for P50, 200 + kms to <30 kms for P70, with +2.11% Daily Active Users,+2.27% Content Interactions and +1.51% Cold Users gains
Education
University of Mumbai
Bachelor of Engineering (B.E.), Information Technology
2010 — 2014
St. Andrew's College of Arts, Science and Commerce
High School, Computer Science
2008 — 2010
University of Washington Information School
Master’s Degree, Information Management - Data Science
2016 — 2018
Skills
- Sql Server Management Studio
- C++
- Mysql Workbench
- Data Structures
- Css
- Javascript
- Node.js
- Extract, Transform, Load (Etl)
- Html
- Mysql
- Microsoft Office
- C
- Programming
- Sql
- Linux
- Planview
- Core Java
- D3.js
- Informatica
- Software Development
- Python
- Microsoft Sql Server
- Powerpoint
- Microsoft Excel
- Research
- Machine Learning
- Ajax
- Databases
- Management
- Cascading Style Sheets (Css)
- Natural Language Processing
- Tableau
- Database Design
- Deep Learning for Java
- Microsoft Word
- Project Management
- Java
- Micr
- Leadership
- Power B
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