About Me

I am aspiring Data Scientist pursuing Master's degree in Data Science major at Stony Brook University, New York. I developed passion for Large Language Models and Big Data Analytics in my MS journey, and move forward to collaborate with professionals in these fields. I want to focus on solving real-world challenges, driving impactful results and grow professionally. I am eager to contribute to the evolution of the Data Science field and discover unrevealed data. Lets connect to explore data in all possible ways and invent new scientific skills to study the "word".

Skills

Experience

Education

  • Programming Skills
    Python | R | Java | SQL | OCAML | SAPBW
  • AI/ML Libraries
    PyTorch | TensorFlow | SciKit-Learn
  • Cloud and Data visualization
    Snowflake | CloudLab | Azure | PowerBI | SAP Analytics Cloud | Matplotlib | Seaborn | Plotly
  • Systems Engineer, Infosys
    Jul,2022 - Dec,2023
    As a Systems Engineer at Infosys I specialized in SAPBI and worked for the client company P&G, here's an overview of my work experience:
    1. Data Pipeline Optimization & Monitoring:
    I monitored and optimized process chains and pipelines, ensuring efficient and accurate data flow into the SAP BW warehouse, skills I now apply to streamline data pipelines in data science workflows.
    2. Extraction, Transform and Load(ETL):
    Expirenced in global ETL processes to ensure efficient data load operations, server health, and error resolution across multiple time zones using SAPBW Workbench, enhancing data pipeline reliability.
    3.Advanced Tools & Learning:
    With hands-on expertise I have done certain certifications in SAP Analytics Cloud,SAP ABAP, Snowflake, Microsoft Azure and SAP BW, complemented by training in Java and DBMS
  • Master's in Data Science
    Jan,2024 - Present
    Stony Brook University, New York
  • Bachelor in Technology
    Jun,2018 - May,2022
    Electronics and Instrumentation Engineering
    Adikavi Nannaya University, Andhra Pradesh, India

Certifications

Mastering Generative AI-A Simple Guide for Beginners

In this certification, I got to learn basic Generative AI, Large Language Models, Transformers. I implemented downstream tasks, fine-tuned LLM'S in Python

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Snowflake

Expertise in building scalable data pipelines and optimizing data workflows in Snowflake.
Proficiency in designing, managing, and optimizing Snowflake data warehouses for efficient analytics.
Skilled in implementing data lakes on Snowflake, ensuring seamless data ingestion and management.

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Functional Programming Language: OCAML

I learned fundamental principles of functional programming, including immutability, referential transparency, the power of higher-order functions, syntax and semantics of OCaml Language
Type Inference and Polymorphism
Pattern Matching
Recursive Thinking

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P&G SAP ABAP Developer

Issuer: Procter & Gamble
Issued: Aug 2023
Credential ID: ET5045
Summary: Certified in SAP ABAP development, showcasing expertise in building and optimizing enterprise applications. Earned while working at Infosys.

Projects

NCAA-March-Madness-Basketball-Tournament-Outcome-Prediction-Model

NCAA basketball game is very famous, predicting the outcome of tournament is interesting game, but applying machine learning skills to predict outcome is much more interesting. This project is forecasting the outcomes of both the men's and women's 2024 collegiate basketball tournaments, a portfolio of brackets based on historical data. I used Logistic Regression, Random Forest, Gradient Boosting, and K-NN to predict models and attained some accuracies regarding the dataset.

Exploratory Data Analytics-Airbnb Listings

This project performs Exploratory Data Analysis (EDA) on New York Airbnb Listing 2024 data to uncover trends and patterns in rental listings. I used Python Jupyter Notebook to do EDA and used libraries like Pandas, Numpy, Matplotlib, and Seaborn for cleaning, visualization, and analysis.This project offers valuable insights into the New York Airbnb market, helping both guests and hosts make informed decisions.I identified key trends and developed actionable recommendations

Quantum Search Algorithm on Weighted Databases

This project implements an Adaptive-Grover-Algorithm using Qiskit, analyzing different dataset distributions and producing visualization results. Analysis and implementation reveal the adaptive quantum search nature compared to linear search. Addressed key challenges in designing an adaptive Grover search compared to original algorithm, explained results on real-world weighted data. The project provides a few enhancements to the original Grover’s search implementation strategies and scalability of the algorithm

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Contact me

gayatrisivani3010@gmail.com

+1-9342464724

View My Resume

Copyright Gayatri Sivani Susarla