Tenet Healthcare

AI Product Director

Trilliant Health

Developed machine learning models to predict various data points in our claims and provider datasets. My role among them was:

• working with Health Plan Price Transparency (HPPT) data to develop a proprietary Rate and Quality Score for payers and providers to enable users to identify who the high-quality *and* affordable providers are
• using machine learning to predict providers' taxonomy classification to enhance our Provider Directory product using claims and NPPES features
• using claims data to infer patients' Primary Service Area (PSA) to enhance many of our products - like our Demand Forecast, Provider Directory, and Network Explorer reaching a ~47% increase in classification accuracy

Data Scientist IV

Unum

• Developed and implemented the company’s first ever AI Governance Framework, aligning AI with enterprise compliance goals and ensuring bias mitigation, model transparency, and reproducibility
• Led the zero-to-one vision, strategy, roadmap, and execution of NLP and AI projects, building scalable AI products across different functional domains while ensuring executive buy-in
• Consistently lead user interviews to discover common pains, needs, and friction points to better inform AI projects

Principal AI Product Manager

• Lead zero-to-one AI projects through Product Discovery, Delivery, and Iteration, while using best Build-Measure-Learn practices
• Orchestrated the cross-functional launch of a scalable NLP-as-a-Service platform (backed by LLMs and GenAI) to address document classification, semantic matching, entity extraction, and summarization leading to a 54% increase over baseline models, a 73% average time savings of common manual processes which drove an annual cost savings of $2.5M
• Championed quick experimentation and iteration on AI initiatives, leading to quicker development and release cycles
• Drove executive buy-in of AI products through heavily-researched operational usability, engineering feasibility, and business viability analyses

Senior Data Scientist / AI Product Manager

Nashville Software School

Data Science Instructor - Assistant (One Cohort)

The General®

•     Led end-to-end 0-1 product development and data science execution across multiple Claims-focused ML initiatives, managing roadmaps, feature definitions, and integration with core systems
•     Identified and prioritized high-impact ML use cases in collaboration with cross-functional stakeholders, translating business needs into scalable predictive models
•     Mentored and coached junior data scientists while also setting standards for model development, engineering best practices, and product delivery
•     Designed, developed, and deployed Silhouette, an internal ML infrastructure tool that automates cloud-based environment setup (AWS), version control (DVC/S3, Git/Bitbucket), and reproducible ML workflows (Pipenv, Cookiecutter)
•     Scaled internal tooling and drove cross-team adoption of Silhouette, reducing friction in deployment and improving reproducibility across ML projects

Lead Data Scientist

•     Shaped data science team vision, product strategy, and foundational infrastructure - establishing the team’s first tech stack, creating its first public-facing AI blog, and launching its first internship program
•     Led zero-to-one development of NLP product using claim notes (Word2Vec, LDA Topic Modeling, Concept Mining) to predict attorney involvement, delivering $2.3M in business savings
•     Built and trained a deep learning model (PyTorch) to classify vehicle damage from claim images, enhancing adjuster workflows
•     Used OCR to extract structured text from scanned claim documents to identify and surface specific types of claim denials
•     Developed a REST API web app to support labeling workflows, enabling scalable image annotation for model training
•     Owned product lifecycle and modeling for a total-loss vehicle prediction system, driving $2.5M in annual cost savings

Data Scientist II

• Perform various natural language processing tasks (R/tidytext, Python/gensim), including sentiment analysis, topic modeling, and Word2Vec/Doc2Vec
• Build a nation-wide price elasticity model using a Mixed Effects/Hierarchical Logistic Regression algorithm (with cross classified and nested random effects) to predict demand for a product at various pricing structures (R, Julia)
• Predict a claim's route by converting claim notes to Word2Vec word embeddings and feeding those word vectors into machine learning models for multi-class prediction (Python/Gensim/Scikit-learn)
• Build an interactive geo-spatial smoothing app (Python/Flask, PostGIS, Leaflet.js) for various key performance indicators using AWS S3 as the data store
• Collaboratively design and implement statistical techniques and machine learning models with team members and department heads
• Create pipeline to transfer data from SQL Server database on local server to PostgreSQL database on AWS EC2 instances
• Assist the data science team in transitioning from local servers to cloud computing on AWS
• Architect and implement RESTful APIs (Python/Flask, Celery, Redis, SQL) that expose various statistical models for consumption

Data Scientist I

Perception Health (Acquired by Huron)

•	Built machine learning models (Python) that used lab data to predict if a patient would be admitted or not and visualized results using an ROC curve and confusion matrix
•	Worked alongside Perception Health's Principal Data Scientist to analyze physicians’ referral patterns and consult hospitals on how to best reduce out-of-network referrals
•	Used GIS (PostGIS, Leaflet.js) techniques to visualize healthcare trends geographically
•	Lead production on Perception Health's flagship product since March 2015 to the present
•	Built customizable, interactive dashboards (Leaflet.js, D3.js, Crossfilter.js) into the primary platform
•	Optimized SQL queries and data preparation for faster graph rendering and page-load times
•	Utilized Agile methodologies (JIRA) to organize releases while ramping up features
•	Worked with the lead architect to optimize SQL scripts across the primary product's platform
•	Converted the platform to a RESTful API for more efficiency and to decouple the server-side code from the client side templates
•	Designed and developed an internal SQL application (Python, Flask) for non-programmers to easily upload data into a database, making repetitive communication with the database faster and more memory efficient

Software Engineer Project Lead

Perception Health

• Built machine learning models (Python, scikit-learn) that used lab data to predict if a patient would be admitted or not and visualized results using an ROC curve and confusion matrix
• Worked alongside Perception Health's Principal Data Scientist to analyze physicians’ referral patterns and consult hospitals on how to best reduce out-of-network referrals

Data Scientist / Software Engineer

Relode, LLC

• Designed and wrote programs that efficiently scraped useful data from various websites using Python and created web applications to be used internally by Relode sales representatives to access this data.
• Uploaded and maintained captured data in a MySQL database.
• Wrote Python scripts that reformated and correctly structured raw, unstructured data.

Software Developer (Contractor)

Digital Reasoning

• Parsed corrupted XML files in Python using ElementTree and Regular Expressions in order to pin point the corruption
• Designed and wrote programs that efficiently cleaned and structured the corrupt data in order to increase the accuracy rate of the firm’s predictive models

Checkd.in

• Employed web-parsing techniques to convert unstructured, raw data into a workable format to perform statistical analyses
• Utilized Facebook's Social Graph API to scrape useful data
• Designed and wrote programs that parsed and statistically analyzed Facebook data using Python

Software Developer (Intern)

Building data products @ Gridsearch | Principal DS @ Trilliant Health

I partner with businesses to bring data and AI-centric products and features to market. 

I also build machine-learning apps with and for my sons. Currently, I’m building a Natural Language Understanding app I call LADNER (Locating Assignments and Dates using Named Entity Recognition) that locates homework assignments and due dates on his teachers’ websites and emails, and then automatically adds them to my Trello calendar daily so we don’t miss homework assignments or quizzes. 

Before that, I built a machine-learning app called Achoo that predicted my son's inhaler usage using air quality, weather, and allergen data.

In my career and hobbies, I build machine learning and data-centric software that makes life easier.

💡Timothy Dobbins💡

Data Moves Me, LLC

Consulting and freelance data work, DS/ML course creation, influencer marketing for ML/AI solutions.

Founder

MoneyGram International

Head of Decision Science

Comet

Developer Advocate

UC Berkeley Extension

Instructor of Data Science

EMERITUS Institute of Management

Faculty & Data Science SME

Constant Contact

Senior Data Scientist

Vistaprint

Analytics Manager – eCommerce Analytics
Recruited to managing a team of analysts delivering actionable insights to optimize the site experience and conversion.
•	Owner of Global Testing Governance, proactively identified interactions between tests across teams before launch.
•	Leading the Adobe Analytics tagging effort as we move to a new site and new site flow.
	Questioning and analyzing every part of our website.
•	Helped write an R package to allow quick analysis of split-run tests.

Analytics Manager – Product Analytics
Promoted to work as part of a global team (based in London), managing one direct report.
•	Increased efficiency by identifying multiple new opportunities to create self-service tools for the marketers, data aggregation in SQL, dashboard delivery in Excel.
•	Trained 60 analysts on how to perform Regression Analysis and Full Factorial MVT test analysis.

Analytics Manager

•	Created an actionable behavioral segmentation of the Digital customer base using Cluster Analysis
•	Evaluated opportunities for testing.
•	Used SQL to fulfill complex data requests.
•	Created a way to evaluate the 5-year value of a new digital customer for use in channel marketing decisions.
•	Created a method for valuation of new products added to our pipeline.

Lead Analyst

Silverlink Communications

•	Delivered market research, segmentations, research posters, and communication campaigns designed to support managed care organizations (MCOs), pharmacy benefit managers (PBMs), and disease management (DM) clients.
•	Analysis involving various regression methods/crosstabs/decision trees
•	Presented results to the client
•	Manipulation/analysis of large/complex datasets in SQL 
•	Developed surveys/analyzed survey results/perform tests of statistical significance



Co-authored a poster presentation that has won best in show on Reducing Ethnic Disparities for Colorectal Cancer Screenings:

Stream P, Clark C, Kehrer K, O’Brien CE, Newsom J. Reducing Ethnic Disparities for Colorectal Cancer Screenings. Poster session presented at: AcademyHealth 2013 Annual Research Meeting. 2013 Jun 22‐25. Baltimore, MD.

Analytics Consultant

NSTAR

•	Built Neural Network models to forecast hourly electric load
•	Developed numerous econometric time series analysis models to help plan for load planning and capacity
•	Performed statistical analysis for various departments within the organization

Forecast Analyst

AI Developer Advocacy & Data Science | The Cool Data Projects Show | Data Moves Me, LLC | LinkedIn Top Voice

Co-author of "Machine Learning Upgrade: A Data Scientist's Guide to MLOPs, LLMs, and ML Infrastructure" with Wiley. It's available for preorder now: https://a.co/d/95jx7QP

I've been a data scientist since finishing my MS in Applied Statistics in 2010. It all started with building neural nets and ARIMAs in the utility industry, then I moved to building models for winback campaigns in healthcare, but the majority of my data wrangling, model building, and hypothesis testing has been in marketing analytics in e-commerce.

I’d say that the 4 years I spent heavily hypothesis testing UI, product and marketing changes was probably my favorite.  Consumer behavior is fascinating.  The most important thing I learned is that customers sometimes do things that make no sense, so don’t make assumptions, use data.

More recently I've ventured into working with image and text data.  I built a school bus detector using YOLOv8, and I'm currently building an LLM-powered app for a healthcare use case.

taplio

The Battle

💡Timothy Dobbins💡

Kristen Kehrer

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