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Resume

Experience

epiFi Technologies Pvt. Ltd.

Fintech, Neobanking Startup by Gpay Founders

Data Scientist [June 2020 - Present]

  • I joined here as a part of the top@50 early members of the organization and second in the data science team. I built core features and structured the data science team, making the new-generation millennial banking experience more personalized and user-friendly.
  • Setup MLOps components: Airflow for Automated Model Pipelines, Data Version Control, BentoML for Model Inferencing system, Kibana for Logging
  • Responsibilities
    • Hiring best talent for the company
    • Mentoring Interns and Freshers in Data Science team
    • Business requirements understanding, communicating metrics and helping leadership team in taking data-driven decisions
  • Problems Solved:
    • Ranking of Users on Fi Waitlist using Multi-Criteria Decision Making Article Link
    • Retaining Users on Waitlist by sighting them with our feature Insights powered by NLP Data Science Model. Here we look up the user's merchant mails and extract price using a NER Model. Example of an Insight from this feature: "You have spent 10000 in the last 3 months at Amazon." making users aware and conscious of their online spending. Product Demo Link
    • Understanding customer support requirements and helping customer support agents by automating the issue categorization process. Issue categorization helps us know the friction points of our product. Powered with Zero-Shot-Classifier Model and list of predefined issue tags.
    • Improving in-app help using data by making changes to the help screen so one can find answers faster. To make it easier to find the right answer after landing on the wrong search result, added 'Related articles.' such that related articles are semantically similar to the one you are currently reading. Then this entire flow of finding related articles is automated by Airflow.
    • Based on user-features Demographics, Geographics, Technographics Features, Income, etc. group users to find accurate user peer groups using K-Prototypes clustering Model. Outcome: Over this peer group show personalised user-insights.

1mg Technologies Pvt. Ltd.

HealthTech, e-pharmacy platform

Data Scientist [Feb 2019 - June 2020]

Problem Solved:

  • On product pages of 1mg, we showed a Similar Products List which was to improve platform diversification by allowing a user's to explore and exploit the platform. This similar product widget was powered by BERT-word embedding on meta-data of the product.
  • Personalized Recommendation of Products using Neural Collaborative Filtering, this personalized recommended list in comparison to the Popular Products list increased Add To Cart by 32% and CTR by 38%.
  • Worked on the entire homepage metric pipeline from setting up CTAS queries on Athena to Scheduling Script on Airflow with a flock webhook that posts daily metrics.
  • Worked on Trending Products Widget on Search, which is on ZScore Moving Average idealogy. It helped us gain 60% orders by this widget when compared in A/B test with a popular product list. Medium Blog
  • Finding Disease Trends time series analysis.
  • Ranking reviews by relevance: sorting reviews by relevance. Research Paper Link
  • Worked on search algorithm enhancement, reduced unsupported search by 20% using NLP methods, LDA, TextRank and TF-IDF on product descriptions to extract related keywords and phrases.
  • Worked on Product Filter Tags automatic generation for products that helps customers to easily find a product on our page. Filter Tags on Left Side of Category Page
  • Multilabel Classification, Auto Categorization of Products to different Categorizes using product features like color, name, uses, product form, ingredients, etc.
  • Creating an NLP library that has the ability to pre-process data, extract features, do phonetic matching, string matching, get readability score, etc.
  • Awarded First Data Science Sprint Hero @1MG Link

InterviewBit/Scaler Academy

Edtech platform

Data Scientist (SME) Subject Matter Expert [Nov 2018 - June 2020]

  • InterviewBit is an E-learning Platform (Top #10 startups of India by LinkedIn) which also conducts hiring challenges.
  • For Machine Learning/ Data Science challenges, I have been their problem setter and subject matter expert. This experience taught me a lot, I got to work on different problems like Text Classification, Text Summarization, Keyword Extraction from Text, Regression and Classification problems. Created 14+ problems for InterviewBit which were used in Pan India competitions of which in one of them, more than 200k+ developers participated.

Skills

Programming Languages

Framework, Tools and Services

Data Platforms used

Professional Skills
Python Airflow PostgreSQL Natural Language Processing
SQL Data Version Control Athena Time Series Analysis
C++ BentoML and Cortex Snowflake Automation with Selenium
PySpark MLFlow S3 Machine Learning
FastAPI Cockroach DB Data Analysis
AWS DynamoDB Data Visualisation
Kibana: Monitoring and Logging
Metabase: Analytics tool

Education

Jaypee Institude of Information Technology

Bachelors of Technology (Hons.) - Computer Science (CGPA - 8.6)

Research Papers

  1. Uppal, S., Jayal, A., & Arora, A. (2019). Pairwise Reviews Ranking and Classification for Medicine E-Commerce Application. LINK
  2. Uppal, S., Jain, A., & Arora, A. (2020, January). Comparative analysis for keyterms extraction methods for personalized search engines. In 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 358-363). IEEE. LINK

Data Science Video Courses by Shaurya

  1. Dezyre: Ecommerce product reviews - Pairwise ranking and sentiment analysis
  2. Dezyre: Demand prediction of driver availability using multistep time series analysis
  3. Antwak: Insightful Data Science Talk

Awards

  • Got awarded 4 times sprint champion at 1mg
  • Best paper presentation award in IEEE Conference: Confluence 2020
  • Awesome Open Source Projects - PyWhatsapp LINK