Greater Chicago Area
I am a senior leader, advisor and data science practitioner with a career formulating innovative solutions that leverage technology and data. I've inspired, influenced, and led the creation of hundreds of digital products; working from both inside and alongside teams of researchers, scientists, designers, engineers and enthusiasts. To learn more about my past project work please visit ➡ https://kevin-hartman.io SKILLS • MLOps, LLMOps, ML Lifecycle Processes and Machine Learning Systems Design • Data Platforms, Product Roadmapping, COEs and Data+AI Strategy • Distributed data processing and petabyte-scale machine learning pipelines • Deep learning with computer vison and large language models (LLMs) • Exploratory data analysis and feature engineering for applied machine learning • Quantitative methods for statistical analysis • Experimental design and causal inference • Effective visualizations / design for human perception / storytelling with data • Edge devices, device prototyping and IoT • Cloud/data platforms and serverless technologies • Domain-driven design, microservices and event driven architectures • Planning, defining and managing large-scale enterprise solutions • Agile practitioner and certified scrum master • Lean product: value-prop, jobs-to-be-done, business model canvas and user journeys • Career learner with a focus on strategic thinking and creative problem solving • Visual storyteller, facilitator and team builder • Top 10 CliftonStrengths: Responsibility, Learner, Restorative, Achiever, Belief, Relator, Communication, Arranger, Futuristic and Adaptability TECH • Apache Spark, PySpark, Spark SQL, Spark Structured Streaming, Delta Live Tables • Keras, TensorFlow, PyTorch, PyTorch Lightning, Sklearn, MLlib, LLMs, HuggingFace • Databricks Lakehouse, Redshift, BigQuery, Synapse, Oracle, SQL Server • Kafka, Message Brokers, ESBs, Apache NiFi, Airflow, Kubeflow, MLFlow • Databricks Workflows, Vertex AI Pipelines, Sagemaker Pipelines, Azure Data Factory • GCP, Azure, AWS, Cloud Infrastructure, Terraform • Domain-driven Design, Microservices, REST, Docker, Yaml • Object-oriented Design, TDD, BDD, CI/CD, Jenkins, GitOps • Python, R, Java, JavaScript, C#, C/C++ • Relational SQL, OLAP, NoSQL • Jupyter, Anaconda, RStudio, Sagemaker, Vertex AI, Azure ML, PyCharm, VSCode • Matplotlib, GGPlot, Tidy, Seaborn, D3.js, Altair, Tableau, Adobe Illustrator • IoT, Device Programming, Edge Computing • Linux/Ubuntu, Bash, Git; Windows and MacOS
Leading the Lakebase for Application Development initiative that defines a new database architecture category for the industry and changes how agile development teams work with databases by introducing copy-on-write database branching into the developer workflow. I lead a team of Partner Solutions Architects working with global and regional consulting partners across GenAI, Lakebase, Agent Bricks, and Apps to develop solutions for customers and create Champions of the Databricks Platform.
Establishing the Databricks Data Intelligence Platform and the industry defining Lakehouse within customers of all shapes and sizes. I lead an incredible team of Partner Solutions Architects that work with global and regional partners to develop GenAI and Analytics solutions for customers, create Champions of the Data Intelligence platform, and solve some of the world's toughest data problems.
Teaching Data Science Capstone where students bring together the knowledge and skills learned throughout the Masters of Information and Data Science program to execute a full end-to-end data science project. Through ideation, selection and project execution, students learn to integrate knowledge from different courses, demonstrate proficiency in data collection and analysis, identify target user audiences, and develop comprehensive data science and professional skills. Effective communication of data-driven findings and the ethical application of AI in solutions is also emphasized.
• Provided advice and assistance to a cohort of 150+ students per term through scheduled Office Hours.
• Grew our Data Science staff 20% and increased our ML Engineering staff 5-fold. • Contributed to $14M in sales through solutions. • Brought three net-new accounts to the organization. • Developed repeatable solutions for clients tailored to each stage of their Data+AI journey. • Directly recruited Data Scientists and ML Engineers into the organization through my personal brand and network. • Advanced the skill and development of our team through practice meetups, book clubs, paper readings, show and tells, one-on-ones, mentoring, creating personal training paths and leading by doing. • Created sales and marketing assets, presentations, proposals, SoWs, and drove opportunities to close by providing thought leadership, subject matter expertise, and right-sized solutions. • Implemented an evaluation problem for new Data Science recruits conducted over a live session between candidate and interviewer with pair programming to immediately assess technical skill, consulting acumen and critical thinking abilities. Databricks Partnership • Socialized, enacted, and led our partnership with Databricks and nurtured it to a burgeoning program. • Coordinating partner training events, developing programs, and managing certifications for our Data Engineers and ML Professionals to maintain our partnership status. • Actively managing activity with our shared accounts, facilitating meetings, events, sponsorships, and assembling joint go-to-market programs. • Enjoying deep professional relationships with Partner Sales Directors, Account Executives, Solution Architects, Managing Directors and GMs/VPs at Databricks. • Certified Databricks Machine Learning Professional and invited Databricks Champion. Client Work 👇
• Recruited and led a team of graduating Data Science students to participate in the United Nations World Innovation Day Hackathon in April 2021. The hackathon brought together diverse teams from around the world to create solutions in support of the United Nation’s Sustainable Development Goals. • Our submitted solution, Carby, is an easy-to-use mobile tool that recommends low carbon alternatives to products a consumer would purchase normally. The tool utilized trained image recognition models and carbon footprint scoring on products captured from the user’s mobile device camera to recommend alternatives. • The solution won first place among several thousand submissions in the international competition. • Pursued commercialization of product with partners and venture capital
Providing Digital Solutions at the intersection of Business Strategy, Value Proposition and Technology Innovation Client Work 👇
Designed experiments and developed machine learning algorithm to detect high risk clauses in legal contracts leveraging Large Language Models (LLMs) from HuggingFace.
Managed delivery of a large-scale CRM solution with third party data integrations for a global industrial packaging manufacturer.