About

Work Experience

• Data Scientist, Keyspire

  Jan, 2025 - Present

  Sole technical specialist at a 30-person company, independently owning the full data ecosystem — from CRM governance and automation pipelines to predictive analytics strategy and executive reporting.

  • Architected a centralized HubSpot CRM framework; cleansed, validated, and deduplicated 190K+ contact records, establishing a trusted single source of truth across marketing, sales, and fulfillment.

  • Owned the product roadmap for Keyspire's predictive analytics initiative, scoping and prioritizing LTV forecasting, churn prevention, and segmentation systems in direct collaboration with executive stakeholders.

  • Built executive and operational dashboards translating complex CRM and pipeline data into actionable insights for non-technical stakeholders; automated reporting workflows saving hundreds of team hours annually.

  • Leading the productionization and launch of the Keyspire Investor Tool — inheriting a Replit prototype, migrating to a GitHub-managed codebase, connecting a production database, and deploying to Render; currently implementing authentication ahead of a live member release.

  • Served as acting technical and finance department lead for one month; independently conducted technical screening interviews for data roles.

  • Partnered with executives to design and implement company-wide data governance policies ensuring accuracy, security, and scalability.

• Data Scientist (Capstone Project), St. Louis Blues Hockey Club

  May, 2024 - Jul, 20242 months

  Developed predictive machine learning models for sports analytics classification tasks in collaboration with the NHL organization.

  • Developed and optimized three supervised learning models (Gradient Boosting, Feed-Forward Neural Network, and Random Forest) for game outcome classification.

  • Engineered 28 custom features — including 5 novel features and 16 normalization features — improving model signal quality, reducing class imbalance bias, and strengthening data representation.

  • Increased core success metric (Balanced Accuracy) by over 3x through hyperparameter tuning, regularization, and iterative feature engineering; validated predictions against real-world outcomes.

  • Solved complex data challenges including extreme class imbalance, missing values, and fuzzy name-matching across multi-source datasets.

• Research Data Analyst, St. Joseph's Hospital

  Sep, 2018 - Dec, 20191 year 3 months

  Supported psychiatric research through data collection design, database management, and statistical analysis.

  • Contributed to strategy and methodology for two in-development research papers in collaboration with clinical research leads.

  • Built a repository of 150+ psychiatric medications and generics sourced from public health datasets; streamlined health data workflows using REDCap and SPSS.

Projects Experience

• Sleep Stage Classification (EEG Wave ML Pipeline)

  - Present

  Built an LSTM-based machine learning pipeline to classify sleep stages from EEG brainwave signals.

  • Implemented feature engineering from EEG frequency bands.

  • Built sequence-to-sequence LSTM models in PyTorch.

  • Applied custom cross-validation and threshold optimization.

• LAPD Crime Data Analysis

  - Present

  Exploratory analysis of Los Angeles Police Department crime datasets using Python, statistical modeling, and visualization to identify patterns in crime frequency, location, and reporting trends.

  • Cleaned and analyzed public LAPD crime datasets using Python (Pandas, SciPy, StatsModels).

  • Performed exploratory data analysis to identify crime patterns across locations and time.

  • Built visualizations using Altair to communicate crime trends and distributions.

  • Applied statistical analysis to derive insights from large public safety datasets.

Skills

Education

Interests