Data Analyst and Data Science Graduate

Aaron Binder

Dallas, TX • *************@*****.*** • 214-***-****

linkedin.com/in/aaronbinder81 • github.com/aaronbinder81

PROFESSIONAL SUMMARY

Data Analyst with a completed M.S. in Data Science with hands-on experience in Python, SQL, and statistical modeling, plus 10+ years of analytical and reporting work in fast-paced operational environments. Recently engaged in a Data Analysis Internship supporting database reporting and program audits at the Dallas Holocaust and Human Rights Museum. Skilled in data cleaning, exploratory analysis, machine learning pipelines, and translating complex data into actionable insights for non-technical audiences.

TECHNICAL SKILLS

•Programming & Analysis: Python (pandas, NumPy, scikit-learn, PyTorch, matplotlib, seaborn), SQL (PostgreSQL), R

•Machine Learning: Regression (linear, ridge, logistic), classification, neural networks, NLP, ML pipelines, custom transformers, grid search, cross validation, model evaluation (precision/recall, F-beta, ROC), feature engineering

•Statistical Analysis: Hypothesis testing, exploratory data analysis (EDA), multinomial logistic regression, descriptive statistics, outlier handling

•Databases: PostgreSQL schema design, CTEs, joins, subqueries, aggregation, query optimization, primary/foreign keys, data cleaning in SQL

•Visualization & Reporting: Power BI, matplotlib, seaborn, ggplot2, Excel (advanced formulas, pivot tables, dashboards)

•Tools: Git, GitHub, Jupyter Notebook, pgAdmin, VS Code

EDUCATION

Eastern University — St. Davids, PA

M.S., Data Science

Relevant Coursework: Machine Learning, Applied Machine Learning, Natural Language Processing, Statistical Modeling, Data Mining, Database Systems, Big Data Analytics, Data Visualization, Data Engineering, Ethics in Data Science

University of North Texas — Denton, TX

M.S., Molecular Biology

Austin College — Sherman, TX

B.A., Biology

PROJECTS

Data Science 2025 Salary Study

Python • PostgreSQL • Regression Modeling

•Collected and analyzed real-world data science job posting data to identify compensation and skill demand trends across roles and experience levels

•Designed PostgreSQL schema and wrote advanced SQL queries using CTEs, joins, and aggregations to extract structured insights from raw posting data

•Built regression models in Python to evaluate relationships between technical skills, years of experience, and total compensation

•Created visualizations and dashboards to communicate findings to non-technical audiences

ML Pipeline for Census Income Classification

Python • scikit-learn • Custom Transformers

•Built end-to-end machine learning pipeline using scikit-learn ColumnTransformer with custom transformers for categorical encoding and numeric scaling

•Implemented ridge regression with grid search hyperparameter tuning to optimize model performance

•Coded classification metrics from scratch (accuracy, precision/recall, F-beta, ROC curve) and verified outputs against scikit-learn implementations

BRFSS Health Survey Analysis (R)

R • ggplot2 • Multinomial Logistic Regression

•Conducted full statistical analysis on the CDC BRFSS 2021 dataset, including data cleaning, EDA, descriptive statistics, and outlier handling

•Built multinomial logistic regression model with prediction outputs to evaluate health-behavior relationships across demographic groups

•Produced ggplot2 visualizations and presentation-quality outputs designed for accessible interpretation

Bitcoin Transaction Data Analysis

PostgreSQL • Time-Series Analysis

•Imported and cleaned historical Bitcoin blockchain transaction dataset using PostgreSQL

•Wrote advanced SQL queries with CTEs, aggregations, and date filtering to calculate transaction fees, volume, and USD transfer value

•Performed time-series analysis of blockchain activity trends across multiple market cycles

PROFESSIONAL EXPERIENCE

Dallas Holocaust and Human Rights Museum Feb 2026 – Jun 2026

Education Data Analysis Intern

•Performed structured data entry and validation for educational tour and programming datasets used by the Learning and Curriculum team

•Analyzed records from the Upstander Education Database to support a comprehensive lesson and resource audit across the museum's full curriculum library

•Created internal data reports summarizing program usage, lesson coverage, and educational resource metrics for leadership review

•Identified gaps and inconsistencies in program tracking records and recommended process improvements to standardize future data collection

•Collaborated with curriculum staff to translate operational reporting needs into structured data requirements

•Supported improvements to data tracking processes for education programs, scheduling records, and resource inventory

•Documented data definitions and reporting workflows to support knowledge transfer and ongoing team use

Optomi Professional Services Aug 2024 – Dec 2025

Senior Technical Recruiter

•Maintained and validated large recruiting datasets across the applicant tracking system, supporting operational reporting and executive review

•Generated KPI dashboards and performance metrics in Excel using advanced formulas and pivot tables to track sourcing and placement activity

•Identified and corrected data inconsistencies prior to executive-level reporting, improving the reliability of weekly and monthly leadership reports

•Analyzed pipeline conversion data to identify bottlenecks across the candidate funnel and inform sourcing strategy adjustments

•Partnered with hiring managers and account leadership to translate hiring goals into measurable recruiting metrics and reporting requirements

•Standardized data entry practices across the team to improve dataset consistency and reduce reporting rework

Business Centric Technology Jan 2023 – Aug 2024

Lead Technical Recruiter

•Analyzed recruiting funnel metrics and workforce data to reduce time-to-fill by 20% across technical placement roles

•Built dashboards tracking pipeline conversion rates and sourcing performance across multiple client accounts and role categories

•Performed weekly trend analysis on candidate sourcing channels to identify the highest-yielding pipelines and reallocate sourcing effort

•Developed structured reporting templates that became standard team-wide for client-facing pipeline updates

•Trained junior recruiters on data hygiene practices and ATS reporting workflows, improving consistency of pipeline data across the team

•Forecasted hiring capacity using historical placement data to support quarterly account planning and revenue projections

Amazon May 2022 – Jan 2023

Full Lifecycle Technical Recruiter

•Conducted workforce funnel analysis to identify candidate drop-off patterns across stages of the interview pipeline

•Delivered talent market insights and hiring trend reports to leadership using internal recruiting data and external benchmarks

•Managed full-cycle recruiting and maintained structured candidate pipeline datasets in proprietary tracking systems

•Partnered with hiring managers across multiple business units to translate technical role requirements into measurable sourcing criteria

•Used data from previous hiring cycles to forecast pipeline depth needed to meet hiring targets within fixed timelines

Consulting Solutions, Inc. Dec 2020 – May 2022

Lead Technical Recruiter

•Forecasted hiring needs using historical recruiting data and built Excel-based dashboards to monitor pipeline metrics across roles and client accounts

•Standardized reporting datasets used by leadership to track sourcing effectiveness, recruiter performance, and hiring progress across accounts

•Analyzed candidate pipeline conversion data to identify bottlenecks and reallocate sourcing resources toward highest-yield channels

•Partnered with account managers to translate client hiring goals into measurable sourcing criteria and structured reporting requirements

GTN Technical Recruiting May 2020 – Dec 2020

Senior Technical Recruiter

•Designed sourcing analytics workflows that improved outreach effectiveness by 30%, reducing time spent on low-yield candidate channels

•Maintained reporting datasets used to track hiring metrics, recruiter performance, and sourcing channel effectiveness across client engagements

•Produced talent market insights using ATS pipeline data to guide client hiring strategy and benchmark compensation across technical roles

Strive Consulting Jan 2018 – Mar 2020

Lead Recruiter

•Recognized with the 2018 Red Plate Award (Employee of the Year) for exceptional performance, team contributions, and client outcomes

•Developed internal metrics dashboards in Excel to track recruiting activity, placement rates, and hiring performance across the team

•Led recruiter performance reporting and workforce analytics, providing leadership with structured data summaries to guide team planning

•Standardized ATS data entry practices and reporting templates across the team, improving consistency of pipeline data used for client updates

DAVA Oncology Jul 2017 – Jan 2018

Recruitment & Operations Coordinator

•Maintained structured recruiting datasets to support operational reporting and track candidate and hiring activity across medical affairs roles

•Built Excel-based tracking systems using advanced formulas and pivot tables for recruiting pipeline forecasting and operational headcount reporting

•Coordinated recruiting operations and scheduling logistics for a specialized oncology staffing function, supporting both clinical and administrative hiring

TriNet Pharma Dec 2015 – Jun 2017

Medical Affairs Recruiter

•Implemented LinkedIn Recruiter workflows and sourcing analytics to improve candidate identification efficiency for specialized pharmaceutical and medical affairs roles

•Managed full-cycle recruiting across clinical, regulatory, and medical affairs functions; maintained candidate tracking data used for pipeline visibility and reporting

•Built and maintained Excel-based tracking sheets to monitor open requisitions, candidate status, and hiring timelines across multiple concurrent searches

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