Griffin Salyer

Leader and Data Scientist

I am a Data Scientist passionate about advanced and functional analytics and leadership in an evolving technical world. My passion for Data Science and leadership intersect to create my drive for actionable insights and mentorship of those around me. I began my career as a Mathematical Economics and Applied Mathematics double major at Hamdpen-Sydney College, and then entered the Masters of Science in Business Analytics (MSBA) Data Science program at The College of William and Mary. After graduating I moved into the pharmaceutical industry specializing in operations with a distinct focus on providing functional insights, customer segmentation and behavior prediction, and partnering heavily with salesforces to drive the bottom line. I moved into the Fortune 500 Enterprise world of Data Science and Finance at Markel Group, where I have had the opportunity to pioneer data infrastructure and build end-to-end Data Science and Applied Machine Learning solutions. Throughout every project and career turn, I purposefully employ a kind, emphatic, enthusiastic, and uplifting attitude.

My vision is to provide insights that guide data-driven business decisions at every turn - boosting the access to curated data for key decision-makers while pioneering a sustainable infrastructure and flexible data environment.

My Data Science toolkit includes a variety of tools, skills, and specializations that enhance my competencies. A few highlights are below:

• Expert Python, R, and SQL for applications in Data Science and Engineering
• Advanced Visualization and Curated Insights for Executive and Senior Leadership
• At Scale Applied Machine Learning, Deep Learning, and Predictive Modeling
• Software Suites for Reporting, Automation, And At Scale Insight Communication
• Proven Track Record of Partnership, Collaboration, and Communication at Executive and Senior Leadership Levels
• Consistent and Purposeful Mentorship and Leadership at all Levels
• Fortune 500 Enterprise Production-Level Modeling and Engineering Lifecycle, Iterative Development Cycle & CI/CD At Scale

Core Skills: Data Science, Machine Learning, Predictive Modeling, Artificial Intelligence, MLOps, DevOps, Version Control(Git), Data Analytics, A/B Testing, Data Visualization, Business Intelligence, Predictive Analytics, Forecasting, Communication & Collaboration, Leadership, Mentorship, Storytelling with Data, Critical Thinking, Cross-functional Teaming and Organization, Project Management & Ownership
Domain Knowledge: Finance, Insurance, Pharmaceuticals, Investments, Cryptocurrency, Sales, Marketing, Operations, Supply Chain, Customer Segmentation, Customer Behavior Prediction, Accounting
Explicit Programming: Python, R, SQL
Visualization Tools, Supplemental Programming: Django/Flask/Dash, Streamlit, HTML, Javascript, CSS, SCSS, Tableau, PowerBI, Matplotlib, Seaborn, ggplot, R Shiny
Core Data Concepts & Engineering Databricks, Azure DevOps, Agile Methodologies, OOP, Test-Driven Development, Functional Programming, API & Model Serving and Development, Pandas, NumPy, Polars, Scipy, SparkSQL, Hadoop, ETL, Data Warehousing, Data Engineering,Redshift, Microsoft SQL Server, AWS, Google Cloud
Machine Learning & Deep Learning: Scikit-Learn, Caret, Tensorflow, Keras, Pytorch, Spark-ML/PySpark, Supervise & Unsupervised Learning, Deep Learning, Reinforcement Learning, Feature Engineering/Meta Labeling, Model Evaluation and Monitoring, LLMs, NLP, Production Model Deployment, Model Interpretability, Model Explainability, Model Optimization, Model Tuning

The Specialty Analytics and Experimentation Data Scientist role at Markel is responsible for production ready at-scale Predictive Modeling, Advanced Analytics for senior leaders and decision making, Product Line analytics and modeling, Profitability modeling, Risk modeling, and Data Engineering and Infrastructure Design. The team consists of several Data Scientists that continuously learn, lead, and support eachother and the endeavors of Markel Specialty.

• Experimentation and Advanced Analytical Design - Pioneering Specialty Insurance Technology
• Advanced Modeling, Predictive Modeling, LLMs, and Production Model Deployment and Development
• Data Engineering, Architecture, and Infrastructure Design - Data Science & Modeling Applications
• Multi-departmental Partnerships and Collaboration, Leading and Supporting Cross-functional teams to enhance the bottom line
• Mentorship and Leadership in Cutting-Edge Applications of ML, AI, Data Science, and Software Engineering

The Finance and Accounting CCR Unallocated role at Markel is responsible for establishing support for the Finance business through Insight Generation, Predictive Modeling, Data Reporting, Automation, Process Optimzation, and Data Infrastructure Design and Engineering. The role's highlights are below:

• Mission-Critical Process Automation and Optimization
• Reporting Design, Generations, Visualization, and Communication
• Advanced Modeling, Machine Learning, Heuristic Algorithms and Algorithm Design
• Data Engineering: ETL, Infrastructure Design, and Warehousing
• Multi-departmental Partnerships and Collaboration
• Mentorship and Leadership in Developing a Cohesive Data Culture

In this role I pioneered Data Science, Data Infrustructure Design, Engineering, Automation, and Analysis in support of our Ceded Reinsurance departments. I supported the redesign and optimization of established processes, facilitating modern data-centric solutions. Whether collecting data, optimizing processes, or building custom reporting or analytics suites, I collaborated with teams to deliver flexible solutions for mission-critical decision making, processes, and products.

The Business Data Scientist role at Kaleo engages in responsibilities ranging from advanced analytics to partnering with salesforce leadership to design functional tools. The role's highlights are below:

• Process Automation and Streamlined/Automated Reporting
• Advanced Analytics and Insight Design, Generations, Visualization, and Communication
• Advanced Modeling, Machine Learning, Heuristic Algorithms and Algorithm Design
• Data Engineering: ETL, Infrastructure Design, and Warehousing for Downstream Data Science
• Senior Executive and Sales Leadership Partnership
• Mentorship and Leadership of Analysts, External Vendors, and Key Stakeholders

The Commercial Operations department services the commercial business in all things from partnering with our salesforce to collect data and answer practical questions to designing sophisticated models and analyses. The salesforce I supported was large and I frequently partnered with senior leadership to design and implement functional analytical solutions. Additionally, I partnered with internal and external key stakeholders and met weekly with both sales and corporate senior leadership to provide insight and inform corporate strategy.

Below are my old project highlights - starting before my professional career began. Unfortunately, I am not at liberty to share all of my projects, especially my most recent, due to proprietary information and intellectual property rights. I am always happy to discuss their significance in regards to my career and the skills I have developed.

Note: Each project has several preview photos that can be enlarged. Please feel free to contact me with questions on any of the below content.

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Exploratory Introductory Report on Feedforward Neural Nets - Artificial Intelligence

This project provides an introductory explanation of Feed Forward Neural Networks(Artificial Intelligence) through the lens of an exploratory report.

Splines Explanations and Examples

This project provides an introductory explanation of Regression Splines and their different use cases with R code examples.

Pluvio Carry Route Optimization

This optimization project was one of my earliest in optimization for business needs. This project covers how to optimize truck carrier shipping routes to minimize costs. The project is presented in an html reporting format.

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Machine Learning Poly and Step Presentation

This project was designed as a presentation to other Data Scientists and was intended to provide a clear overview of a machine learning procedure. The presentation-style format was created to be accessible by those following along with the lecture.

Machine Learning Zillow Home Prices

This project was developed as an applied machine learning project that used live and recent data to solve a business objective. In this case, we were curious how home prices became established, and what contributed most to the overall price of a home.

Ridge&Lasso Regression

This Project shows a simple explanation, with example R code, of applied Ridge and Lasso regressions.

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Project List

The links shown to the right represent a few examples of projects I have completed over time. Please click on the links to be taken to the specific project listed.

- Simple Artificial Intelligence

- Regression Splines

- Pluvio Carry Route Optimization

- Machine Learning Poly and Step Presentation

- Machine Learning Zillow Home Prices

- Ridge&Lasso Regression

- Best Subset Selection

- Forward Stepwise

- Model Selection

More Coming Soon!

Please contact me if you have any questions about my skills, previous work experience, or any projects I have completed. I am always open for conversations with recruiters about interesting career opportunities and would love to hear about what is available.