Parikshit M.

As a Machine Learning Engineer & Data Analyst with 5+ years of industry experience, I specialize in building end-to-end ML pipelines, transforming complex datasets into actionable insights, and deploying scalable data solutions across cloud platforms. I've worked across the full ML lifecycle from raw data ingestion to model deployment helping businesses make smarter, faster decisions. ✅ Data Analysis & Dashboard Storytelling I don't just build dashboards I turn raw, messy data into compelling visual stories that drive decisions using Power BI, Apache Superset, and Excel. I design interactive dashboards that go beyond charts clearly showing what the numbers mean, what's trending, and what actions to take next. ✅ Machine Learning & Predictive Modeling Developed ML models for use cases including ethnicity prediction using US Census data, product likelihood scoring, and balance sheet forecasting with Time Series models. Applied classification, regression, clustering, and NLP algorithms using Python, PySpark, and XGBoost. Leveraged AutoML and Hyperopt for model selection and hyperparameter tuning, optimizing for F1 scores. Managed experiment tracking and model registration using MLflow. ✅ MLOps & Pipeline Orchestration Designed and deployed scalable ML pipelines using Azure Data Factory (ADF) and Databricks, with seamless integration with ServiceNow and email alerts. Built Feature Pipelines creating Silver and Gold layer tables. Applied OOP principles and PySpark pipeline wrappers for production-grade inference. Experienced with Docker, Evidently, and MLflow for end-to-end MLOps. ✅ Cloud Platforms Hands-on experience across Azure (DevOps, Data Factory, Databricks), GCP (Cloud Run, Cloud Build, BigQuery, Artifact Registry), AWS (Databricks, S3), and Snowflake for scalable data and ML workloads. ✅ NLP & Text Analysis Applied NLP techniques including sentiment detection, keyword extraction, and text classification using Python. Experienced in building models for text categorization. ✅ Web App Development & Deployment Built and deployed a Market Mix Modelling web application on GCP Cloud Run using Flask and Node.js, enabling marketing budget allocation across social media platforms with full cloud infrastructure support. Tech Stack at a Glance: Power BI · Apache Superset · Python · PySpark · SQL · MLflow · XGBoost · Scikit-learn · FastAPI · Flask · Azure ADF · Databricks · GCP · Snowflake · Docker · Hyperopt · AutoML Let's connect and build intelligent, data-driven solutions for your business!