Haby Sow
Statistician
Charlotte,NC
Summary
Analytical statistician with expertise in SAS, R, and Python, specializing in data integrity, quality control, and reporting for national studies. Proven ability to streamline workflows, develop impactful data visualizations, and provide actionable insights to support strategic decision-making. Adept at collaborating with cross-functional teams to maintain high data quality standards.
Overview
4
4
years of professional experience
4
4
years of post-secondary education
Work History
Statistician
Research Triangle Institute, RTI International
Research Triangle Park, NC
05.2024 - Current
- Contributed to the Primary Care First (PCF) Project by assisting in roster review and quality control to ensure data integrity. Developed and executed SAS programming for various reports, enhancing data reporting efficiency. Supported the creation of the PY24 Sample Frame, refining the sampling process. Collaborated on PCF PECS, streamlining workflows through Sample Summary and Contractor Delivery reports.
- Substate Analysis (NSDUH-SAE): Created substate letter attachments and tracked responses, ensuring efficient stakeholder communication and data collection for the National Survey on Drug Use and Health (NSDUH) Small Area Estimation (SAE) model. Conducted variable checks and quality control tasks to uphold data accuracy.
- Imputation Team Collaboration (NSDUH): Assisted in PMN hot deck conversion from SAS to R. Reviewed NSDUH report chapters to ensure a comprehensive understanding study objectives. Contributed to race and Hispanic indicator imputations, as well as employment-education imputation efforts, improving overall dataset quality.
- NuMoM2b Heart Health Study II – SAS to R conversion: Led the transition from SAS to R, translating complex SAS macros into efficient, reusable R functions. Worked with large demographic and enrolment datasets (>10,000 rows), leveraging dplyr, tidyverse, and haven to clean, merge, and prepare data for analysis.Automated workflows by developing custom R functions, standardising variables, and optimising dataset merging using dplyr joins. Enhanced workflow automation using R’s vectorised operations, reducing processing time and improving performance.Designed R functions to summarise baseline variables, generate frequency tables, and calculate descriptive statistics. Validated translation accuracy by comparing SAS and R outputs with comparedf function, achieving 99% accuracy.Collaborated with statisticians and analysts to refine methodologies, delivering precise data insights that drive better decision-making.
Research Analyst
HelioCampus
Chapel Hill, NC
05.2022 - 08.2022
- Employed advanced research analysis with the HelioCampus benchmarking model to categorize employee job descriptions and access time allocation.
- Provided support to the Client Services Team, contributing to the successful completion of technical tasks related to data analysis reporting, and Excel-based data management.
- Prepared and delivered impactful research reports and presentations for internal audiences, enhancing understanding of global online learning trends and strategies.
- Expertly organized complex labor data in higher education by employing ETL processing techniques using Python pandas,resulting in a 30% enhancement in data organization and accessibility.
Statistical Analyst
North Carolina Central University, NCCU
Durham, NC
05.2021 - 05.2022
- Conducted comprehensive literature reviews on topics related to food insecurity and social capital during the COVID-19 pandemic.
- Executed data mining, cleansing, and transformation of a 1,500-row dataset on food security in North Carolina using Stata and R.
- Generated analytical reports and captivating data visualization on Stata that succinctly conveyed insights from exploratory data analysis, resulting in a 15% improvement in report clarity.
- Analyzed results from regression analyses and hypothesis testing on R Studio and Stata to identify social determinants affecting food insecurity.
- Attained a remarkable 90% predictive accuracy for food insecurity in North Carolina by applying the Rasch Model in food security analysis.
- Presented analytical findings and recommendations to mentors and senior leadership, significantly influencing strategic decisions regarding social programs and interventions.
Education
Bachelor of Science - Statistics And Operations Research
University of North Carolina At Chapel Hill
Chapel Hill, NC 08.2019 - 05.2023
Skills
Programming Languages: SAS, R (dplyr, tidyverse, haven), Python (Pandas, NumPy, SciPy, Matplotlib), SQL, Stata, MATLAB
Data Analysis & Manipulation: Data validation, quality control, data integration, ETL processes, statistical modeling
Workflow Automation: SAS macros, R functions, vectorized operations
Data Visualization & Reporting: Tableau, Excel (Pivot Tables, VLOOKUP)
Experimentation & A/B Testing: Evaluating experiments to measure product changes
Data Logging & Documentation: Communicating and documenting data requirements
Predictive Modeling & Statistical Analysis: Building models to understand user behavior and growth
Statistical Methods & Modeling: Strong foundation in statistical techniques
Problem-Solving: Ability to translate business questions into data problems
Collaboration & Communication: Working with cross-functional teams
Critical Thinking: Providing feedback and making data-driven decisions
Self-Motivation & Initiative: A self-starting approach to learning and contributing
Timeline
Statistician
Research Triangle Institute, RTI International
05.2024 - Current
Research Analyst
HelioCampus
05.2022 - 08.2022
Statistical Analyst
North Carolina Central University, NCCU
05.2021 - 05.2022
Bachelor of Science - Statistics And Operations Research
University of North Carolina At Chapel Hill
08.2019 - 05.2023