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Meenakshi Ramamoorthy

@meenakshiramamoorthy

Staff Data Analyst/Engineer at Hypersonix building retail and eCommerce data pipelines with Python, SQL, Snowflake, and Airflow.

India

Message

At Hypersonix, I design and maintain data pipelines for retail and eCommerce using Python, SQL, Snowflake, and Apache Airflow. I work across ingestion, transformation, validation, and downstream delivery.

I build reusable analytical data models and OLAP structures, and develop automation for file processing, Snowflake loading, and operational checks. I also implement data-quality and reconciliation processes.

Earlier, as a Data Scientist at PARK GLOBAL HR SERVICE / PATHFINDER BUSINESS ANALYSIS, I developed property analytics models in R, including regression models for sale-price prediction and classification models for building-condition categories.

At RX DATA SCIENCE PHARMA SOLUTIONS, I developed drug-quantity forecasting models using Python, ARIMA, and Bayesian techniques. As a Data Scientist Trainee at INFOFACES, I developed R-based time-series forecasts for base-station utilization.

Experience

Work history, roles, and key accomplishments

Current

Staff Data Analyst/Engineer

Current

Hypersonix

Apr 2019 - Present (7 years 6 months)

Design, develop, and maintain scalable ETL/ELT pipelines for retail and eCommerce data using Python, SQL, Snowflake, and Apache Airflow. Lead end-to-end data engineering workflows and implement automated data quality and validation processes.

Python SQL Snowflake Airflow ETL ELT Data Pipelines Data Validation Data Quality Automation Git GitHub Pandas Data Modeling OLAP Data Warehouse

Data Scientist

Park Global HR Service / Pathfinder Business Analysis

Jul 2018 - Apr 2019 (9 months)

Developed machine-learning solutions for real-estate and property analytics using R. Built regression and classification models to predict property sale prices and identify building-condition categories.

R Machine Learning regression Classification Logistic Regression Decision Trees Random Forest SVC data preprocessing Feature Engineering EDA Model Evaluation

Data Scientist

RX Data Science Pharma Solutions

Jan 2018 - Jul 2018 (6 months)

Developed drug-quantity forecasting models using Python and time-series analysis. Applied ARIMA and Bayesian forecasting techniques to historical pharmaceutical datasets.

Python Time Series Analysis ARIMA Probabilistic Forecasting Data Preparation Trend Analysis Forecasting Model Validation

Data Scientist Trainee

Infofaces

Jan 2017 - Dec 2017 (11 months)

Developed time-series forecasting models for base-station utilization using R. Applied ARIMA, Holt-Winters, and Exponential Smoothing techniques to forecast network utilization.

R Time Series Analysis ARIMA Holt Winters Exponential Smoothing Data Preparation EDA Model Evaluation