Data Analyst Machine Learning

Nithin Bojja Data Analyst

Illinois, USA +1-773-***-**** **********@*****.*** LinkedIn

SUMMARY

Data Analyst with 3+ years of experience in data analytics, machine learning, business intelligence, and data engineering across the healthcare, financial, and technology sectors. Proficient in data visualization, predictive modeling, statistical analysis, and real-time analytics, with a strong ability to transform raw data into actionable insights. Experienced in designing and optimizing ETL pipelines, automating workflows, and implementing AI-driven solutions to enhance decision-making and operational efficiency. Skilled in SQL query optimization, big data processing, and cloud-based analytics to support high-impact business strategies. Adept at ensuring HIPAA, GDPR compliance, and data security standards while collaborating with cross-functional teams to drive innovation and business growth.

TECHNICAL SKILLS

Data Analysis & Visualization: Power BI, Tableau, Looker, Google Data Studio, Matplotlib, Seaborn, Plotly Programming & Scripting: Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Statsmodels), R (dplyr, ggplot2, tidyr, caret), SQL (PostgreSQL, MySQL, SQL Server, Oracle), Shell Scripting (Bash) Big Data & Real-Time Processing: Apache Spark, Hadoop (HDFS, MapReduce), Apache Kafka, Spark Streaming ETL & Data Engineering: SQL Server Integration Services (SSIS), Informatica, Apache Airflow, Talend, Data Warehousing

(Snowflake, Redshift, BigQuery)

Statistical & Quantitative Analysis: Hypothesis Testing, A/B Testing, Bayesian Analysis, Statistical Modelling, Feature Engineering & Dimensionality Reduction

Data Governance & Security: HIPAA, GDPR Compliance, Role-Based Access Control (RBAC), Data Encryption Cloud & DevOps: Amazon Web Services (S3, EC2, Redshift, Lambda), Microsoft Azure (Data Factory, Synapse Analytics), Google Cloud Platform (BigQuery, Cloud Functions), Docker, Kubernetes, Terraform, Jenkins, GitHub Actions, GitLab CI/CD Testing & Monitoring: PyTest, Unittest, Great Expectations, SonarQube, Grafana, Prometheus, ELK Stack Workflow Automation & Scripting: Python Automation (Selenium, BeautifulSoup), Power Automate, VBA (Excel Macros) EXPERIENCE

Data Analyst Universal Health Services (UHS) IL, USA Feb 2025 – Current

Analyzed and optimized hospital workflows, leveraging EHR data, scheduling logs, and resource management platforms to improve operational efficiency and patient experience.

Developed and maintained real-time dashboards in Power BI & Tableau, tracking hospital performance metrics and improving data-driven decision-making.

Designed and implemented predictive models using Python (Scikit-learn) & SQL, enhancing patient admission forecasting and optimizing staff scheduling, leading to a 12% reduction in overtime costs.

Automated data extraction and transformation processes using SQL & Python (Pandas, NumPy), ensuring faster and more accurate data processing.

Optimized complex SQL queries, enhancing data retrieval speed by 50%, facilitating faster decision-making for hospital administrators.

Conducted deep-dive statistical analysis to identify operational inefficiencies, leading to improvements in resource allocation and patient flow management.

Implemented AI-driven workflow optimization strategies, enhancing bed occupancy and staff allocation efficiency to improve hospital operations.

Ensured HIPAA compliance and data security standards, implementing role-based access control (RBAC) to safeguard patient information and maintain regulatory compliance. Data Analyst Intern Universal Health Services (UHS) IL, USA Jul 2024 – Dec 2024

Analyzed and cleaned large healthcare datasets using Python (Pandas, NumPy) and SQL, enabling accurate reporting and improving data quality by 25%.

Built interactive Power BI dashboards to visualize patient trends, readmission rates, and resource utilization, supporting data-driven clinical decisions.

Automated recurring data extraction and reporting tasks, reducing manual effort by 40% and increasing operational efficiency.

Collaborated with cross-functional teams to define KPIs, perform root cause analysis, and support the development of predictive models for patient risk management.

Data Interpretation Analyst Vimta, India Jan 2022 – Dec 2022

Developed and optimized ETL pipelines using SQL Server Integration Services (SSIS) and Informatica, automating pharmaceutical data processing and reducing data ingestion time by 40%.

Analyzed and interpreted complex analytical data from HPLC and GC instruments using Shimadzu and Agilent software, ensuring compliance with FDA and GMP regulations.

Built machine learning models (Logistic Regression, KNN, Gradient Boosting, DBN) to detect anomalies in pharmaceutical quality control data, improving detection accuracy by 30%.

Developed real-time monitoring dashboards in Tableau and Looker, enabling quality control teams to track trends in drug stability and contamination detection.

Automated data validation and reporting workflows using Python and Shell scripting, ensuring 98% data accuracy in regulatory submissions and audit reports.

Designed SQL queries for large-scale pharma datasets, improving drug formulation data retrieval speed by 35% and supporting clinical trial data analysis.

Implemented role-based access control (RBAC) and encryption measures, ensuring secure storage and handling of sensitive pharma research data in compliance with HIPAA and FDA guidelines.

Collaborated with cross-functional teams, including quality assurance, regulatory affairs, and data science teams, to enhance pharmaceutical data integrity and reporting accuracy. EHR Data Analyst CitiusTech, India Jan 2020 – Dec 2021

Extracted, transformed, and analyzed structured and unstructured EHR data from multiple healthcare systems (Epic, Cerner, Meditech) to improve patient experience and retention strategies while ensuring HL7 and FHIR interoperability compliance.

Developed machine learning-driven predictive models for patient churn analysis, reducing churn rates by 20% and enabling proactive interventions based on real-time patient risk assessments.

Designed real-time patient experience dashboards using Tableau and Power BI, providing healthcare administrators with actionable insights, leading to a 30% improvement in patient engagement.

Built and optimized ETL pipelines using SQL, Python (Pandas, NumPy), and Apache Spark, reducing data processing latency by 40% and automating ingestion from multiple data sources, including EHR, patient surveys, and billing systems.

Applied Natural Language Processing (NLP) to analyze patient feedback and sentiment from reviews and surveys, uncovering trends that improved patient satisfaction metrics and provider responsiveness.

Automated patient feedback analytics workflows, reducing manual data processing time by 35% and enabling real-time reporting to improve hospital decision-making and quality-of-care strategies.

Implemented role-based access control (RBAC) and HIPAA-compliant security frameworks, ensuring 100% compliance with patient data privacy regulations and minimizing unauthorized access risks.

Collaborated with data scientists, healthcare administrators, and IT teams to develop AI-driven patient experience insights, leading to a 30% reduction in patient dissatisfaction cases and improved appointment adherence. EDUCATION

Master of Science in Information and Technology In Management Dec 2024 Illinois Institute of Technology, Chicago, USA. (IT) Master of Science in Analytical Chemistry Aug 2022 Vellore institute of technology

Bachelor of Physical Science Aug 2020

Gandhi Institute of Technology and Management

CERTIFICATIONS

Microsoft Certified: Power BI Data Analyst Associate Udemy: 2024 Tableau Certified Data Analyst Training Udemy: The Complete Python Boot camp Zero to Hero in Python

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