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Principal Data Scientist. Part monk, part mechanic. Allergic to nonsense. Devoted to craft.
Building tomorrow's AI before tomorrow shows up. The AI arms race isn't coming. It's already rearranging the furniture while everyone else argues about the floor plan. I help organizations stop doomscrolling the headlines and start writing them. 14 years in, and I still get a kick out of the part where the model actually works. Strategy decks are easy. Anyone with a template and a strong opinion can produce one by lunch. Production systems that move the bottom line on a Tuesday morning when something is on fire? That's the job. That's what I do. I translate generative AI, agentic systems, and MLOps from LinkedIn buzzword soup into things that earn their keep. If a tool doesn't make the business better, I'm not interested in it, and frankly neither should you be. A few things worth knowing: I never stopped building. I write the Python and Golang. I train the models. I break things in staging so you don't break them in production at 2 a.m. while the CFO is on a flight. Kaggle Competition Expert, top 3% globally. Rankings are silly, but the reps that got me there weren't. I build practices, not just projects. I've stood up AI capabilities from a blank whiteboard and grown them into something that shows up in the quarterly numbers. Team builder, collaborator, occasional pain in the right places, lifelong student of the craft. I speak fluent executive and fluent engineer, and I can usually tell within five minutes which one is bluffing. The toolkit, since someone always asks: • LLMs and agents: Claude Code, OpenAI Codex, Hermes Agents, Honcho, LangChain, vector search, prompt engineering, zero-shot modeling. • Classical ML and deep learning: TensorFlow, PyTorch, Keras, HuggingFace, Transformers, Bertopic, ensembles, stacking. • Optimization and AutoML: Optuna, BayesOpt, SigOpt, H2O Driverless, DataRobot, PyCaret. • Forecasting: ARIMA, VAR, Prophe
NYC Data Science Academy
Certified Data Scientist, as recognized by NY State Board of Education
January 1, 2016 – Present
Columbia University
Executive Education, CIO Leadership, Strategic Intuition
N/A – Present
Texas A&M University–Central Texas
M.S., Management Information Systems
N/A – Present
De La Salle University
B.S., Mechanical Engineering
N/A – Present
H2O.ai
Principal Customer Data Scientist, Forward Deployed AI Engineer
May 1, 2022 – Present
Honolulu, Hawaii · Remote
American Family Insurance
Chief Data Scientist, Head of Customer Insights, Data Ops for Claims Services
April 1, 2021 – May 1, 2022
Remote, NJ
Lincoln Financial Group
AVP, Principal Data Scientist, Advanced Analytics
November 1, 2016 – April 1, 2021
Remote, NJ
NYC Data Science Academy
Data Scientist & Advisory Board Member
July 1, 2016 – Present
New York City · Remote
S&P Global
Senior Director, Head of Portal, Content, Data Science Services
January 1, 2006 – January 1, 2016
New York City, NY · On-site
One Call Medical
CTO and Chief Architect
January 1, 2006 – January 1, 2006
Parsippany, NJ · On-site
MetLife
Director, Head of Corporate Portals, Data, and Enterprise Content Management
January 1, 2002 – January 1, 2006
Jersey City, NJ · On-site
Global Crossing
Director, Head of Web Technology and Application Development
January 1, 2000 – January 1, 2002
New York City, NY · On-site
Citi
Vice-President, eCiti Project Manager
January 1, 1999 – January 1, 2000
On-site
Citi
Vice President, Head of US HR Product and Project Management, Lead Architect
January 1, 1997 – January 1, 1999
On-site
Citi
Vice President, Head of Japan HR Ops and Technology
January 1, 1995 – January 1, 1997
On-site
Citi
Vice President, Head of Distributed Systems
January 1, 1990 – January 1, 1995
On-site
Computer Support Group
Manager, Lead Technical Services and Application Development
January 1, 1987 – January 1, 1990
Costa Mesa, CA · On-site
Gen AI 360 LangChain & Vector Databases in Production
Activeloop
June 23, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 23, 2026 – Present
Sequence Models
DeepLearning.AI
June 23, 2026 – Present
Convolutional Neural Networks
DeepLearning.AI
June 23, 2026 – Present
Structuring Machine Learning Projects
DeepLearning.AI
June 23, 2026 – Present
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
DeepLearning.AI
June 23, 2026 – Present
Neural Networks and Deep Learning
DeepLearning.AI
June 23, 2026 – Present
Data Science Certification
NYC Data Science Academy
June 23, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong commitment to data science and AI, with roles evolving from traditional IT management to specialized data science leadership. The diversity of projects across fraud detection, churn prediction, customer insights, and sales propensity modeling, along with experience in various industries (insurance, finance, tech), indicates adaptability and a broad problem-solving mindset. The involvement with NYC Data Science Academy as an advisory board member and instructor, coupled with multiple certifications, demonstrates a proactive approach to learning and contributing to the data science community. This aligns well with a culture that values continuous improvement and knowledge sharing. However, the extensive management background might suggest a preference for leadership over hands-on coding, which could be a factor depending on the specific NLP Engineer role's expectations.
Soft Skills & Operational Fit
The candidate's resume highlights significant leadership and management experience, including leading large teams and driving strategic initiatives. This suggests strong operational fit, project management capabilities, and the ability to influence and collaborate across an organization. Descriptions of driving innovation, working with customers, and presenting workshops indicate strong communication and stakeholder management skills. The experience in Agile methodologies also points to a good fit for modern development environments.