Hey, I'm Mohit Ravindra Kamble,

Specializing in advanced statistical modeling, machine learning, and business intelligence. Comprehensive coursework includes Predictive Analytics, Data Mining, Big Data Systems, Business Analytics, Marketing Research Analytics, Healthcare Analytics, Financial Data Analysis, and Operations Research. Applying theoretical knowledge through real-world projects with City of Boston and Fortune 500 companies across healthcare, pharmaceutical, retail, and marketing domains. Developing expertise in end-to-end analytics solutions from data engineering to predictive modeling and executive dashboarding.

Comprehensive software engineering foundation with focus on database management, programming, data structures, and system design. Developed expertise in SQL, statistical programming, and algorithmic thinking through coursework in Business Intelligence Systems, Data Warehousing, Machine Learning Fundamentals, and Information Retrieval. Built strong analytical, problem-solving, and data modeling skills that provided the technical foundation for my transition into business analytics. Completed projects involving ETL development, dashboard creation, and predictive modeling that sparked my passion for transforming data into actionable business insights.

• Built logistic regression models in Python on AWS SageMaker using Redshift to predict medication adherence from 500K+ patient records, achieving 85% accuracy and improving patient compliance by 34%.
• Created QuickSight dashboards with AWS Comprehend for patient sentiment analysis and Athena queries on claims data for anomaly detection, reducing manual review 70% and identifying $1.2M in fraudulent billing for health insurers.

• Supported migration of 200+ Oracle/MySQL ETL jobs to GCP (Dataproc, Dataflow, BigQuery) achieving sub-hour SLAs; built PySpark framework for Salesforce/PostgreSQL/SQL Server to BigQuery ingestion processing 100GB+ daily.
• Optimized BigQuery via clustering/partitioning/materialized views cutting query costs 45%; implemented Google Data Catalog governance and Python-based GCS archival managing 50TB+ historical data.
• Built Power BI dashboards analyzing 4TB claims with SQL/DAX (YoY, cohort analysis, rolling averages) reducing reporting from days to hours, developed SAS procedures for regulatory reporting enabling self-service analytics.
• Created ML/Python predictive models (Random Forest, XGBoost), and SAS statistical models for patient risk accuracy; developed anomaly detection identifying $500K+ billing irregularities, influencing care strategies for high-risk members.
• Designed HIPAA-compliant dbt marts processing 10M+ records daily with automated testing; built PHI de-identification/tokenization enabling secure cross-team analytics with zero compliance violations.

• Analyzed surveillance data and security patterns to identify potential risks and optimize campus safety protocols.
• Served as a liaison between residents and university resources, facilitating data-driven incident reporting and resolution.
• Collaborated with Public Safety Division, Housing Services, and Northeastern Police to maintain secure living environments.
• Implemented access control measures and conducting systematic security assessments to ensure policy compliance.

• Developed marketing strategies for monthly networking events connecting 500+ tech professionals, managing social media presence, email newsletters, and sponsor communications to build Boston's startup community.