I'm a Data Scientist with a strong background in machine learning engineering, specializing in recommendation systems and pricing models.

🎓 I recently completed a MSc in Computer Science (Machine Learning) at University of Texas at Austin and I'm looking forward to applying machine learning techniques in future projects.

📫 How to reach me: Email | LinkedIn

• Programming Languages: Python, SQL, Go, Bash
• Frameworks: Pandas, NumPy, Scikit-learn, Statsmodels, TensorFlow, Keras, PyTorch, Hugging Face, Spark, Docker, GitLab, Google Cloud Platform (GCP), Google BigQuery, dbt, Streamlit, Apache Airflow, Apache Kafka, Apache Flink, Tableau, Redis, Git, Excel

• Research Projects

  • 3 research projects conducted during my masters

    • Improving Lexical Reasoning of NLI Models

      • Enhanced Natural Language Inference (NLI) models' ability to discern lexical relationships using data augmentation and adversarial training
      • Technologies: Hugging Face (Transformers), Pandas

    • AI Agent for Ice Hockey in SuperTuxKart

      • Developed an image-based AI agent with hand-tuned controllers for playing ice hockey in SuperTuxKart, leveraging Fully Convolutional Networks (FCN)
      • Technologies: PyTorch

    • Real Estate Investment Recommendations

      • Explored machine learning and financial models to provide real estate investment recommendations
      • Technologies: ARIMA, Prophet, PyTorch

• Side Projects

  • Fact Finder Streamlit App
    • An interactive app that leverages OpenAI API to display facts based on user-selected topics and personas
    • You can test the app here: https://fact-finder.streamlit.app/

  Feel free to check out the repositories for more detailed information on each project.

• How GO-FOOD Reads Your Mind

• MSc in Computer Science (Machine Learning), University of Texas at Austin
• BA in Economics, Stanford University

• Specialized in Recommendation Systems, Contextual Bandits, and Linear Programming.
• Senior Data Scientist, Pricing, Gojek (Jan 2020 - Sep 2021)
  • Engineered data and model training pipeline for TensorFlow-based pricing algorithm and linear programming-based price reconciliation, leading to 10% performance uplift in gross profit
  • Developed ML pricing web service in Go that performed experimentation, feature retrieval, model prediction, and price presentation with < 50 ms SLA
  • Applied linear programming techniques to translate government regulations and business constraints into linear constraints within pricing models
• Lead Data Scientist, Recommendations, Gojek (April 2018 - Jan 2020)
  • Led a team of 3 data scientists and data analysts that optimized a food delivery recommendation system
  • Built recommendation model driving 2 million incremental bookings every month and leading to 15% performance uplift versus existing models (Patent No. 10201912472U).

Traveling, hiking, photography, electronic music, meditation.