Data Analyst Public Health

Drona Trital

Chesapeake, VA *****

https://www.linkedin.com/in/drona-trital *********@*****.***

Professional Summary

Data Analyst and Epidemiologist with over 6 years of experience in public health and real-world healthcare data analysis. Expertise in managing and analyzing large datasets, with advanced programming skills in SAS, SQL, R, Tableau and Python. Skilled in creating complex analytical datasets, handling healthcare claims data, and leveraging observational research methods. Proficient in data visualization with Tableau, ArcGIS, and REDCap for survey data, and experienced with military health databases (CAPER, CIDER, GENESIS, DMDC). Holds Secret Security Clearance with a proven track record of delivering accurate, high-quality insights in a secure, compliant environment.

Key Skills

SAS, Python, Tableau, Redcap, ArcGis, MS Excel, Power BI.

Experience in Data cleaning, Analysing, Visualization.

Excellent Analytical and Management skills.

Data Integration, Data mapping, Data Migration, Data Validation, Data management.

Proficient in preparing reports, dashboard, and presentations to effectively convey outcomes.

Logical, Problem solving and critical thinker.

Public Health Process Analysis.

Accuracy and attention to details.

Time management.

Effective under pressure with strong workload management.

Strong written and verbal communication skills.

Experience

Epidemiologist April 2022 - 2024

Department of Defence (DOD) Navy and Marine Crops Public Health Center

Utilized CAPER, CIDER, GENESIS, TMDS, and DMDC datasets to manage and analyze extensive health data on military personnel, with a focus on behavioural and infectious disease trends.

Utilized SAS, SQL, and Tableau to analyze and visualize annual incident and prevalence rates of mental health cases among active-duty service members, creating age-group specific graphs and tables from Mental Health Surveillance reference data.

Leveraged Python libraries such as Pandas for data manipulation and Matplotlib/Seaborn for visual analysis to validate PATCAT/BENCAT codes. This included evaluating the accuracy of military data from CHCS HL7 and Genesis Lab for visualizations to aid researchers at the EpiData Center, Defense Centers for Public Health.

Developed predictive models for outbreak forecasting using SAS, R, and SQL; analyzed patient healthcare events and built cohorts to track healthcare outcomes.

Generated interactive dashboards in Tableau, delivering actionable insights to military health leaders on deployment health metrics and behavioral health patterns.

Performed comprehensive data cleaning on healthcare datasets, ensuring consistency across variables by addressing missing values, correcting outliers, and removing duplicates to improve data quality.

Created Tableau dashboards for military health data, visualizing trends across CAPER and GENESIS datasets, which helped health officials identify emerging health issues and prioritize interventions.

Epidemiologist January 2020 - March 2023

Alabama Department of Public Health

Led the state’s response to the Hepatitis A and COVID-19 outbreaks, using SAS, Python, and Tableau to analyze outbreak data and predict infection patterns.

Coordinated the Vaccine-Preventable Disease (VPD) program, utilizing SAS, Python, and Tableau to analyze immunization trends, produce listings, visual figures, and generate reports for departmental interventions and CDC submissions.

Developed a REDCap surveillance system to track and analyze immunization compliance in public and private schools, using Python to process the data and generate annual immunization status reports for submission to the CDC.

Leveraged SAS and SQL for data quality control, identifying outliers and ensuring accurate submissions to the CDC through the NEDSS system.

Produced detailed visualizations using Tableau and Python, presenting data to state health officials for informed decision-making.

Created custom functions in R and Python for identifying statistical outliers, enabling accurate handling of anomalies and improving data accuracy in epidemiological reports.

Data Analyst / Research Assistance January 2017 – January 2020

Comprehensive Cancer Center, UAB

Analyzed oncology datasets, applying statistical methodologies in SAS and SQL to derive insights for clinical research and build patient cohorts to support evidence-based cancer studies.

Merged datasets from SQL, SAS, and ArcGIS, conducting extensive cleaning to align data from disparate sources, improving the reliability of multi-source analyses.

Documented data cleaning processes for reproducibility, including steps for handling missing data, correcting discrepancies, and managing variable transformations across large health databases.

Analyzed survey results using Excel and SAS to identify trends in breast cancer awareness and treatment barriers in resource-limited settings.

Created detailed reports with actionable insights and recommendations, presenting findings to stakeholders in both technical and non-technical formats.

Projects:

· Adventure Works SQL Data Manipulation:

Conducted advanced SQL queries to extract and manipulate large datasets, uncovering insights and trends across various metrics in the Adventure Works database.

· Covid Case Database SQL Data Extraction:

Utilized SQL to extract and analyze Covid case data from multiple countries, focusing on different case ranges and death statistics to identify key trends and insights.

· Annual School Surveillance Analysis in Victoria:

Cleaned and processed survey data using Excel functions to ensure accuracy and consistency.

Developed SQL queries to understand and analyze the dataset for trends in school immunization compliance.

Created interactive Tableau dashboards to visualize data trends and insights, providing actionable recommendations for health interventions.

- Military Data Score Validation Project (SAS PROC SQL):

Led the validation of scores for the Alcohol Use Disorder Identification Test (AUDIT-C), Post-Traumatic Stress Disorder (PCL-C), and Patient Health Questionnaire (PHQ-8) within the Annual Periodic Health Assessment (PHA) datasets.

Used SAS PROC SQL to query and validate data integrity, ensuring accurate scoring and classification for military personnel health assessments.

Analyzed data trends and discrepancies, providing actionable insights for improving assessment accuracy and supporting health intervention strategies.

- Assessment of DOB, Sex, Service, and Rank Variables (CAPER & SIDR Data):

Led a project focused on evaluating the accuracy of key demographic variables (Date of Birth, Sex, Service, and Rank) in the Comprehensive Ambulatory Professional Encounter Record (CAPER) and Standard Inpatient Data Record (SIDR) datasets.

Conducted data validation and quality checks using SAS and SQL, identifying discrepancies and ensuring consistency across health records for accurate epidemiological analysis.

Provided detailed reports on data integrity, supporting the EpiData Center in improving data reliability for health research and decision-making.

Education

Master’s in Public Health January 2017- December 2028

University of Alabama at Birmingham (UAB)

References

Reference will be available upon request.

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