Work Experience

Data Analyst, Clairvoyant (EXL Company)

  • •Worked as a Data Analyst for HSBC (client).
    • 11/2023 – present
  • •Managed data ingestion and validation using IBM CDC and NIFI Juniper, ETL tools ensuring seamless data flow.
  • •Worked closely with stakeholders to understand business needs and implement data-driven solutions.
  • •Created and configured CDC subscriptions, pipelines, encoding, and mirroring for real-time data synchronization.
  • •Developed Juniper feeds to automate data transfer from Linux to GCP, DB2 to Hadoop.
  • •Utilized SQL extensively for data extraction, validation, and performance optimization.
  • •Optimized data pipelines to improve processing speed and system performance.
  • •Tracked daily tasks and project progress in Jira, ensuring smooth execution and reporting.

    • Data Science Intern , Novartis

    01/2023 – 06/2023
  • •Acquired valuable pharma business insights through collaboration, analysis, and modeling, aiding strategic decision-making.
  • •Developed and delivered a Power app for shipment requirements based on critical feedback from international stakeholders.
  • •Collaborated with stakeholders to understand their needs and translate them into actionable requirements for the app.
  • •Worked on a time series project using company procurement data to predict future price trends.
    • Education

    Masters in Data Science : Fergusson College (CGPA: 7.65)

    2021 – 2023

    Bachelor of computer science : Fergusson College (CGPA:8.38)

    2018 – 2021
    Skills
    Technical Data Skills :

    Python,SQL, Pyspark, Data Analytics, Data Visualization, statistical analytics, CDC, Data management, Excel, Data Mining, Power BI , Database, Optimization techniques.

    Business Analysis Tools

    Microsoft PowerPoint, JIRA, Confluence.

    Machine Learning Models :

    Linear Regression, Logistic Regression, KNN, K Means, SVM, Decision Tree, Random Forest, Naïve Bayes.

    Neural Networks, Word Embeddings, BERT, XGBoost, K-Means Clustering,Reinforcement Learning.

    Projects

    Car Price Prediction and Analysis

  • •Objective : A Streamlit WebApp that can predict price of a used car. Followed, Life Cycle of a Data Science Project.
  • •Tools : Machine Learning | Regression | Linear | Polynomial | Lasso | Ridge | Streamlit
  • •Used Octoparse to Scraped Data from Cars24.com .
  • •Data Cleaning and Feature Engineering.
  • •Performed Exploratory Data Analysis.
  • •Created a Pipeline to fit various Regression Models. And also did Hyperparameter Tuning.

    • Time Series Analysis and forecasting

  • •Objective: A Streamlit WebApp that can automating analysis and forecasting for optimal decision making.
  • •Tools: Machine Learning| Prophet | Streamlit
  • •Used Procurement real business data
  • •Data Cleaning and Feature Engineering,Created pipeline to analysis and forecasting
  • •Performed Exploratory Data Analysis that can help in business decision making