About
Data Scientist & Data Analyst & Data Engineer
I am a data-driven professional with hands-on experience in both Data Analysis and Data Engineering focused on transforming raw data into valuable insights and building scalable data systems. My technical skills include SQL, Python, R, SAS, Power BI, Snowflake, and Databricks, along with cloud experience in Azure.
Currently, I support the U.S. Department of Veterans Affairs through a contract role, where I help improve veteran healthcare engagement by developing predictive models, streamlining data pipelines, and creating dynamic dashboards. I work extensively with large-scale healthcare data, applying statistical techniques and automation to support evidence-based decisions.
I bring cross-industry experience across healthcare, finance, banking, and technology, with a strong foundation in ETL processes, data visualization, and database optimization. I hold a Public Trust Security Clearance and am passionate about using data to create a measurable impact.
- Phone: +1(862) 297 7302
- City: New Jersey, USA
- Degree: Master
- Email: hulyalpagu@gmail.com
Skills
RESUME
• Jersey City, NJ 07306 • +1 (862) 297 7302 • hulyalpagu@gmail.com
Results driven Data Analyst and Data Engineer with strong experience in designing scalable ETL pipelines, building automated dashboards, and delivering actionable business insights. Proficient in SQL, Python, R, and SAS, with extensive knowledge of Azure, Snowflake, Power BI, and Databricks.Skilled in data modeling, pipeline orchestration, and advanced statistical analysis. Proven success in supporting healthcare, financial, banking, and telecom projects with high-impact data solutions. Holds Public Trust Security Clearance.
Professional Experience
Data Analyst
June 2024 - Present
U.S. Department of Veterans Affairs · Contract, Jersey City, NJ
- Developed and maintained ETL/ELT pipelines using Python and Azure Databricks, building star and snowflake schema data models in Azure SQL and Synapse. Automated data validation scripts, improving data quality and reducing processing time by 35%.
- Enhanced veteran engagement and healthcare utilization through advanced Statistical Modeling and Predictive Analytics, utilizing SAS, R, and T-SQL, resulting in a 15% increase in engagement.
- Analyzed healthcare data using Microsoft Excel and T-SQL, applying advanced functions like pivot tables, Vlookup, Xlookup, macros, and Index /Match for data processing and insights.
- Designed and automated 15+ Power BI dashboards, leveraging DAX calculations to provide real-time insights, reducing manual reporting time by 40%.
- Analyzed healthcare data using Microsoft Excel and T-SQL, applying advanced functions like pivot tables, Vlookup, Xlookup, macros, and Index /Match for data processing and insights.
- Conducted A/B testing and hypothesis testing, driving data-backed decision-making that increased operational efficiency by 25%.
Notable Projects:
→Veteran Home Healthcare Project: Leveraged statistical modeling and data analytics to evaluate veteran engagement and healthcare utilization, achieving a 20% improvement in service delivery through targeted insights.
→Employee Certification Healthcare Project: Enhanced healthcare certification tracking, optimizing data processes and achieving a 30% increase in certification completion, improving compliance and operational efficiency.
- Developed and maintained ETL/ELT pipelines using Python and Azure Databricks, building star and snowflake schema data models in Azure SQL and Synapse. Automated data validation scripts, improving data quality and reducing processing time by 35%.
- Enhanced veteran engagement and healthcare utilization through advanced Statistical Modeling and Predictive Analytics, utilizing SAS, R, and T-SQL, resulting in a 15% increase in engagement.
- Analyzed healthcare data using Microsoft Excel and T-SQL, applying advanced functions like pivot tables, Vlookup, Xlookup, macros, and Index /Match for data processing and insights.
- Designed and automated 15+ Power BI dashboards, leveraging DAX calculations to provide real-time insights, reducing manual reporting time by 40%.
- Analyzed healthcare data using Microsoft Excel and T-SQL, applying advanced functions like pivot tables, Vlookup, Xlookup, macros, and Index /Match for data processing and insights.
- Conducted A/B testing and hypothesis testing, driving data-backed decision-making that increased operational efficiency by 25%.
Notable Projects:
→Veteran Home Healthcare Project: Leveraged statistical modeling and data analytics to evaluate veteran engagement and healthcare utilization, achieving a 20% improvement in service delivery through targeted insights.
→Employee Certification Healthcare Project: Enhanced healthcare certification tracking, optimizing data processes and achieving a 30% increase in certification completion, improving compliance and operational efficiency.
Data Science Research Assistant
Nov 2022 - Present
Texas Department of State Health Services · Contract, Jersey City, NJ
- Managed the end-to-end lifecycle of five Data Science projects, including two in the process of
public release, while utilizing Agile Methodology for requirements gathering, planning, design, and
deployment.
- Designed and applied Machine Learning models, including Logistic Regression, K-means clustering,
Gradient Boosting, and Deep Learning, to analyze Healthcare and Financial data for Predictive
Analytics.
- Conducted NLP and Sentiment Analysis using Vader, TextBlob, and BERT to uncover trends in
American song lyrics, leveraging Python (Azure) and Big Data techniques.
- Guided and mentored over 50 students through project completion, resulting in a 25% increase in
on-time submissions and a 30% improvement in overall project quality
Notable Projects:
→ Interpretable Machine Learning Prediction of Mortality: Developed a gender-specific machine learning model with 95% accuracy to predict all-cause mortality, emphasizing the need for gender-specific care, and won the BAASANA Best Presentation award.
→ Bankruptcy Prediction of Companies (Public in IEEE Xplore): Applied Z-Score and statistical modeling (T-tests, A/B testing) to assess bankruptcy risk in the Financial, Technology, and Pharmacy sectors, achieving 92% accuracy and recommending financial tools for improved forecasting.
→ Analyzing American Song Lyrics (In Progress: Public): Used NLP and Big Data techniques to uncover emotional trends in American song lyrics, revealing an 80% prevalence of negative emotions. These insights informed audience engagement strategies and content development.
- Managed the end-to-end lifecycle of five Data Science projects, including two in the process of public release, while utilizing Agile Methodology for requirements gathering, planning, design, and deployment.
- Designed and applied Machine Learning models, including Logistic Regression, K-means clustering, Gradient Boosting, and Deep Learning, to analyze Healthcare and Financial data for Predictive Analytics.
- Conducted NLP and Sentiment Analysis using Vader, TextBlob, and BERT to uncover trends in American song lyrics, leveraging Python (Azure) and Big Data techniques.
- Guided and mentored over 50 students through project completion, resulting in a 25% increase in on-time submissions and a 30% improvement in overall project quality
Notable Projects:
→ Interpretable Machine Learning Prediction of Mortality: Developed a gender-specific machine learning model with 95% accuracy to predict all-cause mortality, emphasizing the need for gender-specific care, and won the BAASANA Best Presentation award.
→ Bankruptcy Prediction of Companies (Public in IEEE Xplore): Applied Z-Score and statistical modeling (T-tests, A/B testing) to assess bankruptcy risk in the Financial, Technology, and Pharmacy sectors, achieving 92% accuracy and recommending financial tools for improved forecasting.
→ Analyzing American Song Lyrics (In Progress: Public): Used NLP and Big Data techniques to uncover emotional trends in American song lyrics, revealing an 80% prevalence of negative emotions. These insights informed audience engagement strategies and content development.
Data Engineer
Oct 2016 - Nov 2018
Dogus Group · Full-time, Istanbul, Turkey
- Built, optimized, and troubleshot ETL/ELT pipelines using PySpark and Python in Databricks and AWS environments, integrating large-scale data into Snowflake and S3 Data Lake.
- Developing Notebooks to extract data in various file formats, transforming, and loading detailed, aggregate data into Snowflake Data Lake.
- Collaborated with teams to design efficient data models (Star and Snowflake schemas) for reporting and analysis.
- Implemented AWS DevOps practices, leveraging AWS CodePipeline and CodeDeploy to build CI/CD pipelines for automated deployment and release management across environments.
- Created interactive dashboards and reports using Tableau enabling real-time insights for stakeholders.
- Built, optimized, and troubleshot ETL/ELT pipelines using PySpark and Python in Databricks and AWS environments, integrating large-scale data into Snowflake and S3 Data Lake.
- Developing Notebooks to extract data in various file formats, transforming, and loading detailed, aggregate data into Snowflake Data Lake.
- Collaborated with teams to design efficient data models (Star and Snowflake schemas) for reporting and analysis.
- Implemented AWS DevOps practices, leveraging AWS CodePipeline and CodeDeploy to build CI/CD pipelines for automated deployment and release management across environments.
- Created interactive dashboards and reports using Tableau enabling real-time insights for stakeholders.
Data Engineer
Aug 2014 - Sept 2016
i2i Systems · Full-time, Istanbul, Turkey
- Designed, optimized, and troubleshot ETL/ELT pipelines using Python, SSIS, and Databricks (Azure environment) to process large-scale datasets, ensuring high-quality, structured data for analytics and predictive modeling.
- Engineered a high-performance Data Warehouse, reducing data retrieval time by 35% and enabling faster Business Intelligence Reporting and advanced analytics.
- Optimized SQL, PL/SQL, and Python scripts, improving Data Processing speed and supporting real-time insights for customer segmentation, fraud detection, and financial forecasting.
- Collaborated with data scientists and analysts, leveraging SQL and Python to prepare clean, structured data for ML Models, enhancing Predictive Analytics in Telecom and banking.
Education
M.S. in Data Science
Saint Peter's University, Jersey City, NY
GPA: 4.0/4.0
B.S. in Computer Sciencee
Kocaeli University, Umuttepe, Turkey
Portfolio
I have shared a selection of complex Data Science projects, including one that is publicly available and two that are nearing public launch, which highlight my expertise in managing end-to-end solutions. I directed and optimized the execution of these projects, overseeing every stage from concept to deployment, including data acquisition, preprocessing, feature engineering, model training, evaluation, and deployment.
- All
- NLP & BIG DATA
- MACHINE LEARNING
- STATISTIC
App 2
App
Dogus Technology, Istanbul, Turkey
- Led full life cycle of Machine Learning products, from data collection, cleaning, and processing to analytics, model building, and deployment; enabled a 15% improvement in model accuracy and a 20% increase in revenue.
- Orchestrated the overhaul of data warehouse structure to enhance storage and querying capabilities; introduced columnar storage format resulting in a 30% reduction in storage costs and a 50% increase in query performance.
- Led the development and maintenance of PL/SQL and SQL queries for ETL processes using SSIS and Oracle Data Integrator (ODI), enhancing data accuracy by 30% and ETL processing speed by 20%.
- Led cross-team efforts to enhance data visualization and streamline processes with Power BI, boosting operational efficiency by 25%.
REFERANS
Saul Goodman
Ceo & Founder
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Sara Wilsson
Designer
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Jena Karlis
Store Owner
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Matt Brandon
Freelancer
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John Larson
Entrepreneur
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Contact
Location:
Jersey City, NJ 07306
Email:
hulyalpagu@gmail.com
Call:
+1 (862) 297 7302