Results-driven AI and data science leader with a track record of building high-performing teams and embedding AI as a strategic capability across organizations. Passionate about driving data literacy so that every level of an organization can make informed, data-driven decisions. Believes AI should augment people, not replace them. Committed to open source foundations that keep organizations flexible, innovative, and in control of their own technology future.

Work experience

Security Benefit - Director, AI & Data Science (January 2026 - Present)

• Build and scale the AI and data science organization from the ground up, hiring AI engineers and senior data scientists to form a high-performing, cross-functional team
• Partner with teams across marketing, operations, actuarial, and sales to identify high-impact AI use cases and deliver solutions aligned to business objectives
• Drive enterprise-wide AI strategy in partnership with executive leadership, aligning AI and data science initiatives with organizational priorities
• Design and deploy multi-agent AI systems that autonomously ingest, classify, and respond to customer questions, reducing manual handling and improving response efficiency
• Build AI-powered tools for senior leadership, including an executive intelligence Slack app that delivers curated news and strategic insights
• Establish production-grade ML infrastructure using Cookiecutter, SageMaker, MLflow, and Git CI/CD pipelines, standardizing model training, deployment, and monitoring at scale across the team
• Champion data literacy across the organization, creating frameworks to help business stakeholders make informed, data-driven decisions
• Establish AI governance standards and best practices to ensure ethical, responsible, and human-centered deployment of AI solutions
• Drive adoption of open source tooling and frameworks to reduce vendor dependency and maintain architectural flexibility

Security Benefit - Principal Data Scientist (September 2024 - December 2025)

• Lead a cross-functional team of data scientists to design and deploy machine learning and AI solutions company-wide, driving innovation and operational efficiency
• Engineered unsupervised ML algorithms to construct detailed financial advisor profiles by integrating third-party data and aggregated sales statistics, significantly enhancing the precision of targeted marketing campaigns
• Designed and deployed an LLM-powered analytics assistant leveraging LangChain, AWS Bedrock, and DataRobot to facilitate conversational EDA and data querying, enhancing the speed and effectiveness of analytics workflows
• Developed predictive models using Python and XGBoost to forecast financial advisor propensity to sell specific products, resulting in measurable improvements in marketing efficiency and conversion rates
• Built an AI-powered call analytics platform utilizing call center data and audio transcripts to provide actionable insights into call center performance; implemented sentiment analysis and call summarization models using HuggingFace, PyTorch, and DistilRoberta
• Collaborated with HR and leadership to define the data scientist role, review applications, and conduct interviews, contributing to the growth and capability of the data science team

ThinkOnward - Senior Data Scientist (May 2023 - September 2024)

• Partnered with clients to define business objectives and translate them into actionable machine learning challenges, delivering insights and solutions via interactive dashboards built with Plotly Dash and Streamlit.
• Led open source initiatives by overseeing maintenance and enhancement of geoscience Python packages on GitHub, streamlining collaboration through effective git workflows.
• Enhanced user experience by developing interactive documentation for a Python package that optimizes drilling rig schedules, improving accessibility and adoption among end users.
• Directed a team of scientists to develop a geophysics-specific foundational model using Vision Transformers and Masked Auto-Encoders; engineered a proprietary masking technique with PyTorch, Numpy, and HuggingFace Transformers, tripling model performance compared to previous benchmarks.
• Boosted 3D synthetic seismic data generation by 50% by parallelizing Python code and integrating AWS Batch, accelerating project timelines and data availability.
• Increased productivity for Shell scientists by 25% by creating a Python script to cluster thin section images and automatically filter out-of-focus samples, streamlining image analysis workflows.

Commerce Bank - Data Scientist (October 2022 - May 2023)

• Managed stakeholder relationships with fraud teams, delivering clear and actionable updates to primary business leaders.
• Developed a PowerBI model performance dashboard that enabled the consumer fraud team to identify $2M in fraudulent transactions; optimized the model’s F1 score to reduce false positives and negatives.
• Collaborated with the consumer credit team in an agile environment to build a credit card acquisition response model, increasing response rates by 30%.
• Extracted and transformed consumer credit data from SQL databases, generating weekly SAS reports to keep stakeholders informed and drive data-driven decisions.

Farmers Insurance - Data Scientist (November 2021 - October 2022)

• Increased profitability of the business insurance portfolio by identifying high wildfire risk policies using ArcGIS and visualizing insights with PowerBI.
• Built and tested policy pricing models in AWS SageMaker using Python and XGBoost; collaborated with team members via GitHub for code sharing and review.
• Designed and implemented ETL pipelines in Alteryx to extract policy data from Snowflake SQL to PowerBI, leveraging DAX and PowerQuery for data cleaning and transformation.
• Generated policy pricing maps using geospatial analytics tools (GeoPandas, GDAL) and integrated third-party customer data for enhanced risk assessment.

Occidental/Anadarko Petroleum Corporation - Senior Geophysicist (May 2014 - November 2021)

• Collaborated with multidisciplinary teams to evaluate Gulf of Mexico prospects, regularly presenting technical progress and recommendations to executive leadership.
• Developed a 3D geologic model for a key hydrocarbon asset using seismic, sonar, and well log data, enabling extended production and saving $120M in abandonment costs.
• Leveraged extracted seismic sensor data and applied Python-based linear regression modeling to accurately predict sand thickness in exploration wells, improving subsurface characterization and drilling efficiency.
• Applied advanced signal processing techniques to 3D seismic volumes, enhancing subsurface imaging and enabling more accurate identification of key geologic features.
• Led technical teams to update geophysical workflows and best practices post-acquisition, ensuring operational consistency and innovation.
• Authored annual technical reports for federal agencies (SEC, BOEM, BSEE), providing reserve justifications and insights into geoscience methodologies.
• Orchestrated a $4M federal lease investment project by synthesizing multi-sensor data and conducting Monte Carlo simulations to assess risk and economics.
• Delivered a 25% ROI on a development well by qualifying reserves through advanced seismic and well data analysis.

Kansas State University - Graduate Teaching Assistant (August 2012 - May 2014)

• Co-developed lesson plans and exams for Introduction to Geology labs in collaboration with department leadership.
• Coordinated schedules and reviewed curriculum for seven graduate teaching assistants, ensuring consistency and quality in lab instruction.
• Taught three lab sections per semester, engaging and supporting 25 students per section through hands-on instruction and personalized feedback.
• Graded assignments and exams for 75 students weekly and provided 5 hours of tutoring per week to enhance student understanding and performance.

Education

• B.S. in Geoscience, Kansas State University, 2012
• M.S. in Geoscience, Kansas State University, 2014

Skills & Tools

• Languages: Python, SQL, SAS
• ML/AI: Machine Learning, Deep Learning, LLMs, Generative AI, NLP, Image Processing, Synthetic Data Generation
• Frameworks: LangChain, HuggingFace, PyTorch, XGBoost, MLflow
• Cloud & Infrastructure: AWS (SageMaker, Bedrock, Batch), Snowflake, Git, CI/CD
• Analytics & Visualization: DataRobot, PowerBI, Alteryx, Plotly Dash, Streamlit
• Domain: Geology, Geophysics, Seismic Interpretation, Seismic Inversion, ArcGIS, GeoPandas

Service and leadership

• Mentor - Big Brothers Big Sisters
• Maintainer - Awesome Open Geoscience GitHub Repository