About Me

  • Driven Data Engineer with 5 years of work experience in Fintech industry, proficient in designing, implementing, and maintaining scalable data pipelines using Python, R, Java.
  • Experience with various data storage solutions such as relational databases (SQL), NoSQL databases (MongoDB), and cloud-based storage (AWS S3, Google Cloud Storage).
  • Skilled in designing and optimizing data warehouse architectures(Snowflake) for efficient querying and analysis. Familiarity with ETL (Extract, Transform, Load) processes and tools (e.g., Apache Airflow, Talend).
  • Strong teamwork and communication skills, ability to collaborate effectively with cross-functional teams, document technical processes and communicate complex ideas to non-technical stakeholders.

    • Contact Details

    Nivetha Balasubramanian
    33 Bay St
    Toronto,ON
    n4balasu@uwaterloo.ca

    Download Resume

    Education

    University of Waterloo, ON, Canada

    Masters in Management Sciences • Sept 2022 - Apr 2024

    CGPA - 3.5/4 Principles of Operations Research, Organizational Behavior, Quantitative Data Analysis for Management Sciences, Applied Economics for Management, Statistical methods for Data Analytics, Operations Analytics, Foundations of Senior Management, International Project Management

    Indian Institute of Technology, Madras

    Diploma in Data Science • Jan 2021 - Apr 2022

    CGPA - 8.7/10 Mathematics for Data Science I&II, Computational Thinking, Statistics for Data Science I&II, Programming in Python, Business Data Management, Programming Data Structures and Algorithms using Python, Machine Learning Foundations, Business Analytics, Machine Learning Techniques, Tools in Data Science, Machine Learning Practice

    SSN College Of Engineering, Chennai

    Affiliated to Anna University • June 2014 - April 2018

    Completed Bachelor of Technology degree from the Department of Information Technology with 29th University Rank and CGPA - 8.63

    Work

    Nasdaq, Toronto,ON,Canada

    Ananlyst - Data Engineering• May 2023 - April 2024

    • Designed and developed an ETL Pipeline using Python, Swagger API endpoints, and SQLAlchemy to pull the data from Nasdaq Risk Platform, to run it over a fine-tuned, quantised LLM Model like Number Station’s NSQL model and Llama2 model using FastAPI to build a chatbot, facilitating customer support in real-time, 42% reduction in man-hours to resolve data related queries.
    • Built a reconciliation system using Python and Swagger API endpoints, to compare traded prices between the Risk Platform and data loaded on the Amazon S3 Buckets using Boto3 packages to handle the data discrepancy and improve process efficiency by 27%.
    • Performed time series analysis like moving averages, exponential smoothing and ARIMA models using Python and SQLAlchemy to observe the trends and forecast the risk exposure value to 72% confidence interval based on historical data.
    • Collaborated with diverse stakeholders like Risk platform clients, developers and product team, to discuss on product enhancement requests and delegate resources.

    Goldman Sachs, Hyderabad

    Technology Ananlyst - Data Engineering• August 2021 - July 2022

    • Designed ETL pipeline to facilitate the movement of structured data by integrating 100 million raw records from 20+ data sources using Python and Java from legacy systems to Snowflake and testing the data quality in batches.
    • Led the database migration from IQ to Snowflake on AWS, resulting in an annual cost savings of $723,000 and improved performance by 18% by utilizing Agile methodology, JIRA and SCRUM framework
    • Worked on supporting the consumers of financial data, such as analysts, data scientists, statisticians and executives to reliably, quickly and securely inspect all of the data available from various sources via ETL pipelines. Also involved in Data Analysis using Python, to inspect the quality of data and retrieve meaningful insights

    HSBC Technology India, Pune

    Senior Software Engineer - Data Science and Engineering • March 2021 - August 2021

    • Leveraged services like Google Kubernetes Engine, Google Cloud Storage, Data Flow and AI Platform on Google Cloud Platform to deploy Machine Learning models like Client Clustering, Product Recommendation systems to improve customer engagements by 57%.
    • Designed APIs for cross-border payments for Payment Initiation, Membership validation and Payment cancellation use cases and tracked them by integrating Swift GPI System using Java and Springboot.
    • Automated the production support issues by designing an alert system on Google Data Studio that improved resiliency by 73%.
    • Developed the infrastructure and pipeline needed to run the Machine Learning Models on Google Cloud Platform, employing Ansible and Jenkins through Terraform scripts.

    Projects

    Import & Export Trade Recommendation as a part of Nation-wide Datathon at HSBC

    Secured second position among 60 teams.Built a Sequential model using Keras to develop a trade recommendation system on Google cloud platform using the historical trade data and other features to fit the Gravitation model.

    Text Translation in Image - Capestone Project in OneFourthLabs

    Developed a model that performs binary classification to understand if an image has text or not, then fed the image with text to a Regression model to get the dimension of text area and perform translation of the text in Hindi to English. Used CNN models with Pytorch to carry on this Deep Learning task.

    Crop Retail Price Prediction system for Farmers as a part of Facebook-sponsored HerTech Hackathon

    Built a Neural Net model using the historical crop data prices with weather and soil factors to estimate the retail prices.Recognised as one of the top 3 teams among 100+ teams.

    Optimised Feature Selection for Early Cancer Detection

    Analysed the performance of Genetic Algorithm combined with classification techniques like Artificial Neural Network, Logistic Regression etc. on the early categorization of Cancer Cells as Benign/Malignant and devised an optimised Feature Selection technique based on the research. Attended National level conference and applied for publication in the journal- “Concurrency and Computational: Practice and Experience”.

    Skills

    Programming

    Python, Java, C, C++, HTML, CSS, Java Script, Nodejs, SQL

    Tools

    Jenkins, Docker, Terraform, SQL, PySpark, Kafka, Jira, Git, Excel, Tableau, Google Cloud Platform, AWS, Snowflake

    Familiar Python Packages

    Numpy, Pandas, Sklearn, Matplotlib, Seaborn, Plotly, Tensorflow, PyTorch, Keras, BeautifulSoup, Scrapy, NLTK, Rasa, PyMongo

    Certifications

    Client Testimonials

    • I had the privilege of managing Nivetha during her long internship and her performance was outstanding. She helped us navigating challenging situations effectively and delivering high-quality work within tight deadlines in an environment using modern and best in class technology. This is without mentioning her mind to innovation. She observed and connected various challenges we faced to bring an idea on how to help the team supporting clients better using machine learning. This was instrumental to build a strong business case for pursuing the effort.

      Myriam Sirieys - Customer Success at Nasdaq

    • Nivetha is exceptionally skilled in Python, Docker, Kubernetes, and Google Cloud. It was a pleasure working with her on a web app project!

      Kalpa Ashhar - Director CTO, Data & Analytics

    Get In Touch.

    For further information, please feel free to contact me !!

    Address and Phone

    Nivetha Balasubramanian
    33 Bay St
    Toronto,ON

    n4balasu@uwaterloo.ca