Trinity Turner

Newly Graduated and ready to continue exploring what the world of data science has to offer!  I have made use of 10+ modeling and algorithmic techniques and hope to apply them to find more real world solutions!

Data Science/Analyst Intern | Goodwill Industries - Charlotte, NC | 01/2025 - Present

• Created a database in SQL to concentrate data from multiple sources into a single database for the department.

• Goal: Enhance effectiveness of Goodwill Training Programs to increase postgraduate employability.

• Questions:  

• How can we maximize skill confidence in those enrolled in Goodwill Training programs from feedback in surveys? 

• What features separate those able to find employment after graduation from Goodwill University from those who                  aren’t? 

• Can we use trainee personal and survey data to isolate problem areas within the program and begin to aid them?

• Utilized SAS and Python libraries (K-means, Linear Reg. ) to identify and minimize hindering factors from trainee data.

• Increased  r  by 2% (from 75% to 77%) by refining feature selection and reducing noise in trainee data.

• Used tools such as Power BI  to create visual reports to investors for GoodWill University programs, expecting detailed insight on program success.

Mental Health App Development (Remote Internship) | Howard University-BRSP - Charlotte, NC | Data Science Researcher                                                                                                         | 05/2023 - 09/2025

• Goal: Use smart watch health data and user anecdotes data to inform those with mental disorders about themselves and possible triggers for prototype.

• Questions:

• To what extent do the combination of physiological indicators explain/align with proclaimed psychological disorders?   

• Can we use user personal data to identify triggers of these behaviors, and possibly predict another event?

• Conducted in-depth research analyzing mental health data to support app development using data manipulation and analysis with Python.

• Created database using SQL and analyzed  data using Python libraries, such as pandas and NumPy. Built and evaluated predictive & classifier models (e.g., linear regression, decision trees) using scikit-learn to identify key variables for app prototype.

• Predicted the general usefulness of variables and improved R² score by 20% (from 0.45 to 0.65) by optimizing feature engineering for mental health predictions.

Bachelors of Science: Data Science and Analytics