Available to hire
I am a Data Scientist with over 3.5 years of experience specializing in machine learning, predictive analytics, and data engineering across public sector, finance, and healthcare domains. My expertise lies in building and deploying ML models, developing scalable ETL pipelines, and designing interactive dashboards to drive data-informed decisions. I enjoy collaborating with cross-functional teams to translate complex datasets into actionable strategies, improving operational efficiency and business outcomes.
Throughout my career, I have implemented A/B testing, customer segmentation, and fraud detection systems while maintaining data integrity and compliance. Passionate about responsible AI and model fairness, I continuously strive to advance solutions that enhance workforce stability, financial product performance, and patient care, ensuring alignment with regulatory standards and executive goals.
Skills
Work Experience
Data Scientist at Baltimore City Public Schools, USA
October 1, 2024 - PresentAnalyzed multi-year employee retention and attrition trends using SQL and Python to develop predictive models that reduced voluntary turnover by 15%. Designed and deployed dynamic Power BI dashboards consolidating over 50 workforce KPIs, enhancing real-time visibility and reducing manual reporting by 30%. Executed A/B testing strategies with HR to improve recruitment campaign effectiveness, boosting candidate conversion by 20%. Built robust ETL pipelines with PySpark and AWS Glue, decreasing data latency by 40% for HR and administrative data sources. Applied K-Means clustering on teacher and staff metrics to target professional development plans, increasing departmental productivity by 25%. Ensured 100% compliance with Department of Education audit standards through data validation. Synthesized data from various systems to uncover systemic gaps leading to policy changes. Developed ML pipelines for early identification of at-risk employees, promoting workforce stability.
Data Scientist at CitiGroup, USA
October 1, 2024 - August 26, 2025Designed and automated real-time fraud detection systems using Spark Streaming, AWS Lambda, and Generative AI-based anomaly detection, reducing false positives by 35% with regulatory compliance. Developed ML models with Scikit-learn and XGBoost to predict credit risk in lending portfolios, enhancing default detection accuracy by 18%. Analyzed transactional data of high-net-worth and institutional clients to inform product recommendations, increasing cross-sell rates by 22%. Implemented customer segmentation via K-Means and DBSCAN for personalized marketing, improving campaign ROI by 27%. Created unified Power BI dashboards from global market data to accelerate senior leadership decisions. Validated model interpretability and fairness with SHAP and LIME, ensuring responsible AI in line with federal audits. Engineered ETL workflows using SQL, Airflow, and AWS Redshift, reducing latency by 45%, and collaborated to design A/B testing frameworks that increased high-yield product placement b
Junior Data Scientist at CitiusTech, India
August 1, 2022 - August 26, 2025Designed and deployed deep learning CNN models for diagnostic imaging analysis (X-rays, MRIs), improving early anomaly detection accuracy by 21%. Engineered RNN and LSTM architectures to analyze time-series EHR data, enhancing patient vitals monitoring and early warning systems in critical care. Conducted large-scale claims and EHR analysis to identify chronic condition progression patterns supporting care management. Built multi-label classification pipelines using Scikit-learn and TensorFlow to predict comorbidities in high-risk patients. Developed interactive Power BI and Tableau dashboards visualizing clinical KPIs, reducing manual reporting by 35%. Automated scalable ETL workflows with Apache Airflow to ingest healthcare data from HL7/FHIR APIs and unstructured clinical notes using NLP, increasing research data availability by 30%. Partnered with data engineers and healthcare experts to ensure HIPAA-compliant PHI handling and optimized ML pipelines on AWS and GCP. Validated ML mod
Data Scientist at Baltimore City Public Schools, USA
October 1, 2024 - PresentAnalyzed multi-year employee retention and attrition trends using SQL and Python, which led to predictive models reducing voluntary turnover by 15%. Designed and deployed comprehensive Power BI dashboards consolidating over 50 workforce KPIs, improving leadership visibility and reducing manual reporting by 30%. Executed A/B testing strategies with HR that enhanced candidate conversion by 20%. Engineered ETL pipelines with PySpark and AWS Glue reducing data latency by 40%, and applied K-Means clustering for target segments achieving a 25% productivity increase. Ensured full compliance with DOE audit standards by validating data integrity and synthesized data from multiple systems to drive executive workforce engagement policies. Developed ML pipelines for early identification of at-risk employees, facilitating proactive interventions.
Data Scientist at CitiGroup, USA
October 1, 2024 - August 26, 2025Designed and automated real-time fraud detection using Spark Streaming, AWS Lambda, and Generative AI, reducing false positives by 35%. Developed ML models to predict credit risk improving default detection accuracy by 18%. Analyzed transactional data to influence product recommendations and increased cross-sell rates by 22%. Implemented customer segmentation with K-Means and DBSCAN, boosting campaign ROI by 27%. Created unified Power BI dashboards synthesizing over 100M+ global records driving faster leadership decisions. Validated model fairness using SHAP and LIME, ensuring regulatory compliance. Engineered ETL workflows with SQL, Airflow, and Redshift reducing pipeline latency by 45%, partnered for A/B testing that increased high-yield product placement by 15%.
Junior Data Scientist at CitiusTech, India
August 1, 2022 - August 26, 2025Designed CNN deep learning models for diagnostic imaging improving early anomaly detection by 21%. Engineered RNN and LSTM models for time-series EHR data enhancing patient vitals prediction and early warning systems. Conducted large-scale analyses of claims and EHR data revealing chronic condition patterns supporting care management. Built multi-label classification pipelines predicting comorbidities reducing readmission risks. Developed interactive dashboards in Power BI and Tableau improving clinical KPI visibility and reducing manual reporting by 35%. Automated ETL workflows ingesting HL7/FHIR and unstructured clinical data via NLP, enhancing research data availability by 30%. Collaborated to ensure HIPAA compliance and optimized ML pipelines in cloud environments. Validated model performance aligning with FDA clinical safety standards.
Education
Master of Science in Data Science at University of Maryland, MD
August 1, 2022 - May 1, 2024Bachelor of Technology in Computer Science at Vidya Jyothi Institute of Technology, India
August 1, 2018 - June 1, 2022Master of Science in Data Science at University of Maryland, MD
January 11, 2030 - May 1, 2024Bachelor of Technology in Computer Science at Vidya Jyothi Institute of Technology, India
January 11, 2030 - June 1, 2022Qualifications
Power BI Data Analyst Associate (Microsoft)
January 11, 2030 - August 26, 2025Power BI Data Analyst Associate (Microsoft)
January 11, 2030 - August 26, 2025Industry Experience
Government, Financial Services, Healthcare, Education, Software & Internet
Skills
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