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💡

Healthcare Outcomes Performance Co. (HOPCo)

As Lead Data Engineer for myrecovery (a HOPCo digital product), I’m responsible for scaling and optimising our Snowflake data infrastructure. I lead initiatives to streamline and enhance data workflows, improve documentation, and ensure our platform supports secure, efficient, and scalable analytics to power better patient care and outcomes.

Lead Data Engineer

CAI Parsable

At CAI Parsable, I engineered and implemented a robust AWS data Lakehouse at CAI Parsable, optimizing the ingestion and processing of Change Data Capture (CDC) data from a transactional Postgres database.

•	Architected an efficient data pipeline using AWS DMS to land RDS Postgres CDC data into S3, then leveraged dbt and Athena to ingest and structure data into Apache Iceberg tables.
•	Successfully integrated the Lakehouse as a central source for data products, achieving notable cost savings and significantly reducing the complexity of data maintenance.
•	Improved observability and monitoring of data product health through the implementation of Datadog.
•	Managed and automated the provisioning of essential AWS infrastructure (S3 buckets, DMS instances, ECS Fargate Tasks, AWS Quicksight Datasets, IAM Roles) using Terraform for consistency and reliability.

Tech stack: AWS (Database Migration Service (DMS), S3, Glue, Athena + Apache Iceberg, ECS Fargate, DynamoDB), dbt, GitHub + GitHub Actions for CI/CD, Terraform, Python, DataDog

Staff Data Engineer

Antonison Consulting Group

Delivered Data Engineering and Architecture solutions at Antonison Consulting Group that enabled client growth and enhanced operational efficiency.

•	Univ. of Florida Bowden Lab (www.bowdenlaboratory.com) - February 2023 to December 2023
    -	Worked with a PhD Student to streamline the processing and management of Mass Spectrometry data. https://github.com/alex-antonison/PFAS-Automated-Quantitation

•	MTSU Data Science Institute (https://mtsu.edu/datascience/) - November 2021 to August 2023
    -	Acted as an in-house technical expert for building scalable cloud data applications in support of research and education outreach initiatives.  Built a data platform to ingest raw data files into a data lake, process into a data warehouse, and serve up results for users within the Environmental Protection Agency.
    -	Built a serverless data lake using AWS S3, Glue, Lambda, and Step Functions for pre-processing the raw sensor and metadata files into a staging location in S3.
    -	Used Athena and dbt run via a Serverless Fargate Task to process the data into a normalized data warehouse and marts.
    -	Built data marts to serve data via dashboards in AWS Quicksight.

•	Concert Genetics (https://www.concertgenetics.com/) - February 2022 to March 2022  
    -	Conducted an assessment and provided actionable improvements in the realms of Data Infrastructure, Data Management, and Data Analytics workflow.

•	Verana Health (https://www.veranahealth.com/) - November 2021 to March 2022 
    -	Advised Verana Health as a Data Solutions Consultant on the architecture and development of a large-scale data lake to ingest data from thousands of EHR systems for their Real World Evidence repositories.

•	Picknic (https://picknic.app/) - June 2020
    -	Assessed the client's existing data ingestion architecture and processes for the Picknic application; advised on industry best practices to streamline data ingestion and improve data management.

Data Solutions Consultant

Nashville Data Nerds

When I took over Nashville Data Nerds, I built the meetup to be around promoting education with working with data. We met monthly where I would bring in conversation leaders to lead conversations around various topics such as skills necessary to be a successful Data Scientist to fairness and bias in AI. After a bit over 3 years, I decided to step down as the organizer and handed the reins over and am happy to see the meetup is better than ever! I recommend checking out all of the events they have going on at https://www.meetup.com/data-nerds/

Community Organizer

Verana Health

Developed a data ingestion platform at Verana Health to extract data from diverse Electronic Health Record (EHR) systems and transform it into a common data model, enabling standardized downstream processing and analysis.

•	Used AWS's Deequ library with PySpark to manage data profiling and quality as data flowed through ingestion pipelines.
•	Built AWS Glue PySpark jobs that ingested incremental data pulls into a staged data layer orchestrated by AWS Step Functions.
•	Developed application templates using cookiecutter that provided a standardized method of creating AWS Glue Jobs and Serverless Applications.  Templates included code for unit testing, generating fake data, and CI/CD configuration files for GitHub Actions.

Tech Stack: AWS (S3, Lambda, ECR/ECS/Fargate, Step Functions, Athena, Glue), Python, Serverless, GitHub

Data Engineer

Stratasan

Cast the technical vision for Data Engineering and Data Science at Stratasan, architecting optimal strategies for managing and scaling data products delivered through both Stratasan's custom application and Tableau.

•	Oversaw the Migration of a data pipeline built with Python and SQL run in Redshift with scaling issues to be rebuilt with dbt and Snowflake. This reduced the run time from days to hours.
•	Supported Stratasan's Tableau instance and provided support to analysts building data products.

Tech Stack: AWS (S3, EC2), Postgres, Redshift, Snowflake, Tableau, Luigi, SQL, Python, Bash, R, data-build-tool (dbt)

Principal Data Engineer

As Data Services Manager at Stratasan, directed the technical vision for Data Engineering and Data Science while mentoring and developing a team of data engineers and scientists. Established streamlined communication channels and intake processes to optimize workflow and project execution for the Data Services team.

•	Worked closely with the Product team to provide technical guidance on enhancing and developing new data products.
•	Implemented a reference data management process that improved control and communication around reference data sets.
•	Provided technical guidance on how to scale data products. This involved identifying new technologies, optimizing data, and automating manual data processes.

Manager of Data Services

axialHealthcare

Drove initiatives to streamline the deployment of models and analyses for the Data Science team. Accomplishments include implementing a specialized data science development strategy, creating an R package to standardize functions, and deploying a unified Redshift datastore. Concurrently, led the ongoing development and enhancement of models focused on optimizing clinical outreach.

•	Improved model and analysis development efficiency by developing and maintaining in-house R and python packages to streamline development actions and feature development. 
•	Improved the deployment of models from development to production by putting in place a source control strategy, environment management, and adding error handling and logging to models.
•	Provided development guidance related to coding practices and source control to fellow data scientists and researchers.
•	Reduced development downtime by ensuring compute resources for the data science team are operating nominally. This includes R Studio Server Pro, JupyterHub, and a Redshift cluster.

Tech Stack: AWS CLI, S3, Postgres, Redshift, Google Big Query, Google Cloud Storage, gsutil, SQL, Python, Bash, R

Machine Learning Engineer

At Axial Healthcare, a startup devoted to combating the opioid epidemic, I contributed to the Data Integration team by enhancing and managing the intake processes for critical client and reference data.

•	Improved client intake process of client data (Medical Claims, Rx Claims, Provider and Member information) by automating aspects of it.
•	Contributed to the development of an enhanced metric engine by coding the data extraction layer in Scala with Spark. 

Tech Stack: AWS CLI, S3, Hive, Presto, Athena, Postgres, Google Big Query, Google Cloud Storage, gsutil, SQL, Talend, Python, Bash, Scala, Spark
Operating Systems: Linux (Ubuntu), MacOS

Fresenius Medical Care North America

At FreseniusRx, a specialty pharmacy supporting End Stage Renal Disease (ESRD) dialysis patients, I enabled various analytic groups and day-to-day operations by developing robust data pipelines, managing data warehousing solutions, and creating and maintaining insightful reporting and dashboard tools.

•	Improved the quality and speed of delivering data and reports to the business by developing scheduled data pipelines using Talend that ETLed application and third-party data into a data warehouse.
•	Increased users' ability to access and utilize data by curating data marts and supporting self-service analytics with PowerBI and Excel (PowerQuery and PowerPivot)
•	Improved visibility into operational and compliance issues by developing automated report alerts that e-mailed stakeholders using SSRS and Talend.
•	Streamlined the extraction and loading of data into Salesforce using Talend in support of call center operations.

Data Environments: SQL Server 2012, Salesforce.com
Tech Stack: TSQL, Talend, Python, R, Excel 2013 (PowerPivot/PowerQuery/PowerMap), PowerBI, SSRS, JIRA, Confluence, BitBucket

Oilfield Instrumentation

Worked in the engineering department of an oilfield drilling instrumentation company and was responsible for supporting software development and client facing products.

* Improved the maintainability and efficiency of customer SSRS report suite.
Accomplished this by optimizing the underlying SQL.
* Supported software development by documenting and replicating software
bugs or feature issues. Would additionally collect changes to business logic if
necessary.
* Interacted with customers to assess possible software issues and provide
technical support.

Data Environments: Microsoft SQL Server (Enterprise - SQL Server 2012)
Operating Systems: Windows 8, Windows Server 2012
Tools: TSQL, SSRS, PowerShell, Team Foundation Server

Data Analyst

KBR Careers - Gov Solutions

Worked as a Data Engineer and Data Analyst in support of the PATRIOT System Effectiveness Model (PSEM), a simulation model of the PATRIOT missile defense system.

* Reduced the time of producing a comprehensive evaluation of PSEM’s
performance in integrated test events from days to a few hours. Accomplished
this with a series of shell scripts that loaded data into the database to queries
that processed and analyzed the results.
* Improved quality of new simulation model by helping design the new data
architecture.
* Helped improve software development efficieny by developing BASH shell
scripts that automated running software test suite and simulation test cases.
* Performed Verification and Validation activities on PSEM, co-authored reports
on the findings, and presented results to PATRIOT project office.

Data Environments: SQL Server 2008R2, SQL Server 2012, MySQL
Operating Systems: Linux (Red Hat), Windows 7
Tools: TSQL, Bash, C#, Excel

Data Engineer with 10+ years of experience delivering data-driven solutions across Government, Healthcare, and Environmental Science. I take a data product-oriented approach, working closely with stakeholders to define clear use cases and build solutions that drive meaningful outcomes. With a strong technical foundation, I can design and implement scalable data platforms that ensure data products are timely, trustworthy, and easy to use.

My core strengths include technical leadership, mentoring, data platform architecture, hands-on delivery, strategic alignment of technical solutions with business objectives, and clear communication of complex concepts to diverse audiences.

taplio

The Battle

💡Timothy Dobbins💡

Alex Antonison

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