Poorya Behnamie
Data Analysis, Visualization, Storytelling
984 291 0073, pooryabehnamie@gmail.com
Chapel Hill, North Carolina, 27516
LinkedIn, GitHub, Portfolio

Professional Summary
Certified Data Analyst with a strong medical background, transitioning from a medical doctor to a data-driven healthcare professional. Proficient in Python, SQL, and Tableau, and well-versed in clinical patient care. Skilled in data cleaning, integration, exploratory analysis, statistical modeling, and data visualization. Passionate about leveraging medical knowledge and data science to enhance patient outcomes and support evidence-based practices. Aiming to apply machine learning models to healthcare data for personalized treatment and improved diagnostic accuracy.

Skills

  • Python: Utilized for data cleaning, wrangling, and integration, enabling comprehensive data analysis. Employed libraries such as Pandas for data manipulation, NumPy for numerical computations, and Matplotlib and Seaborn for data visualization.

  • SQL: Expertise in querying databases, including using SELECT, JOIN, GROUP BY, and HAVING clauses to filter, aggregate, and extract meaningful insights from data. Skilled in PostgreSQL for managing and querying relational databases.

  • Tableau: Created interactive dashboards and visualizations to present complex data insights in an accessible format. Used for storytelling and making data-driven recommendations.

  • Data Cleaning and Integration: Proficient in cleaning datasets by handling missing values, duplicates, and inconsistencies. Integrated data from multiple sources to ensure comprehensive analysis.

  • Data Wrangling: Skilled in reshaping and transforming raw data into a usable format for analysis using Python and SQL.

  • Exploratory Data Analysis (EDA): Conducted EDA to uncover underlying patterns, distributions, and relationships within datasets. Used statistical measures and visualizations to summarize data insights.

  • Statistical and Regression Analysis: Applied statistical methods to analyze trends and relationships within data. Conducted regression analysis to predict outcomes and identify significant predictors.

  • Geospatial Analysis: Used Folium and other tools to create maps and analyze geographic data for spatial relationships and patterns

Medical Skills
Problem-Solving, Attention to Detail, Organization, Documentation, Clinical Reasoning, Physical Examination, Adaptability, Empathy, Active Listening, Medical Knowledge, Teamwork, Medical Terminology, Anatomy, Diagnostic Skills, Medical Research, Multitasking

Projects

Predicting Cancer Incidence and Mortality Based on Socioeconomic and Environmental Factors (June 2024)

Conducted statistical analysis and machine learning modeling to understand the impact of socioeconomic factors on cancer outcomes.

  • Merged datasets from the CDC and County Health Rankings and performed data cleaning and preprocessing using Python.

  • Conducted EDA, geospatial analysis with Folium, and regression analysis to identify significant predictors.

  • Developed visualizations and a Tableau dashboard to present findings on cancer incidence, mortality rates, and socioeconomic influences.

Instacart Sales Analysis and Customer Segmentation (April 2024)
Conducted exploratory data analysis using Python to uncover sales patterns and customer profiles, integrating data from multiple sources.

  • Conducted data consistency checks and derived additional columns to define customer preferences and ordering frequency.

  • Created visualizations to highlight trends, leading to strategic recommendations for targeted marketing and pricing strategies.

  • Delivered insights on peak ordering times, spending patterns, and popular products. Provided a final report on the most profitable customer segments for future marketing.

Rockbuster Stealth LLC Online Service Launch (March 2024)
Analyzed data with PostgreSQL and Tableau to support the launch of an online video rental service.

  • Conducted revenue analysis, calculated rental durations, assessed customer distribution, and identified high-value segments.

  • Used SQL joins, subqueries, and common table expressions to analyze the data and answer significant business questions.

  • Presented strategic recommendations and insights through detailed visualizations.

Preparation for Influenza Season Analysis (January 2024)
Analyzed trends in influenza incidence to inform staffing needs for a medical staffing agency.

  • Integrated multiple data sources to identify high-need states and optimal staffing periods.

  • Conducted descriptive and statistical analyses, visualized findings with Tableau, and presented actionable insights and recommendations to stakeholders.

  • Focused on staffing deployment for peak influenza months and prioritized states with highly vulnerable populations.

Experience

Medical Intern (January 2021–November 2022)
Rasht, Guilan, Iran

  • Developed strong analytical and problem-solving skills by conducting patient interviews and physical examinations.

  • Enhanced communication, teamwork, and data presentation abilities through collaboration with healthcare professionals and presenting patient cases.

  • Ensured accuracy and attention to detail by documenting patient data using electronic medical record systems.

Education

Data Analytics Immersion Boot Camp (November 2023–August 2024)
Career Foundry, Berlin, Germany
Mastered data cleaning, analysis, visualization, and SQL querying. Created interactive dashboards and reports using Tableau.

Doctor of Medicine (MD) (February 2015–November 2022)
Guilan University of Medical Sciences, Rasht, Iran
Relevant Courses: Research Methodology, Statistics, Bioanalysis, Medical Informatics, Business Communication, Public Health Data, Medical Ethics and Law
GPA: 16.83 out of 20