Tom Lorenc

Tom Lorenc Email and Phone Number

Senior Data Scientist @ New York, NY, US
New York, NY, US
Tom Lorenc's Location
New York, New York, United States, United States
Tom Lorenc's Contact Details
About Tom Lorenc

I am an hands on expert in designing and implementing machine learning solutions with a PhD in Computer Science and a patent in machine learning. I am a self-starter who translates business problems into deep learning and generative AI applications. I increased Walmart online sales by 17% with my custom targeted content. Coded open AI and langchain customer service application that answered questions by creating the vector index of documents and similar chunks of data relevant to the question from the vector representation Send the question and the chunks to OpenAI to find the answer. I coded Large language models in NLP for Nike Customer Service AI Chatbot with Azure ML OPs https://www.nike.com/ I built recommendations, with deep experience of A/B testing and OpenAI's model implemented in TensorFlow. https://github.com/tmlrnc/LLMUsed Generative AI, Bert, Open AI, Large Language Models, and LangChain to build prompts and indexes for semantic search and health services automation application that reads medical documents and provides an accurate diagnosis treatment then fills in the prior authorization forms for Price Waterhouse Cooper and Molina Healthcare. https://www.molinahealthcare.com/ Identified patterns and deliver visibility into model performance and training I have a 20 year proven track record of successfully solving business problems with innovative and effective machine learning techniques specializing in LSTM neural nets and natural language processing. I developed machine learning models and deep-dive analyses to solve business problems and make actionable recommendations. Reduced customer churn using Two-Class Boosted Decision Tree and increased customer lifetime value using Boosted Decision Tree Regression. Identified forecasting needs and implemented calculations, scenario planning, sensitivity across data sources and models. Partnered with marketing, sales, finance, brand analytics and brand to stay true to data source insights in forecasting. Managed data team and communications across company.Led and mentored a team of researchers in the field of natural language understanding and reasoning, with a focus on healthcare and biomedical applications. Created a domain-specific healthcare knowledge curation framework for machine understanding and advanced clinical decision support systems and tools for complex disease prognosis, diagnosis, and treatment. Utilized knowledge graphs to solve complex AI tasks, such as deep understanding of clinical text and linking diverse biological data

Tom Lorenc's Current Company Details
HarmonEyes - Healthcare AI

Harmoneyes - Healthcare Ai

Senior Data Scientist
New York, NY, US
Tom Lorenc Work Experience Details
  • Harmoneyes - Healthcare Ai
    Senior Data Scientist
    Harmoneyes - Healthcare Ai
    New York, Ny, Us
  • Harmoneyes - Healthcare Ai
    Senior Data Scientist
    Harmoneyes - Healthcare Ai Jun 2023 - Present
    I designed HarmonEyes AI-powered eye-tracking solution with an AI patent in time series LLM LSTM predictions unleashes the power of eye-tracking & AI in two revolutionary ways: 1) Identify & predict the state of a person based on eye movements in real-time & deliver appropriate interventions to improve user experience and performance fatigue, cognitive load, cybersicknessI designed the SDKs and APIs in Generative AI LSTM to power a wide range of applications forecasting, predictions AI Assistants. Built RAG service platform orchestrations including prompt engineering, guardrails, vector databases, API Ground Truth. Built out a Prompt SDK management service. Designed coded and optimized a classification, forecasting, and recommendation LLM generative AI model with RAG to predict health care eye fatigue and cognitive load with 93% accuracy using LSTM Langchain Pinecone, CNN, classification models, regression models, ensemble, decision trees, clustering Researched latest trends in Deep Learning and Generative AI and apply the same to bring business valueResearched and compared the state of the art Deep Learning and LLM techniques and optimized and scaled the model best fit for the business use case. Consolidated my code from proof of concepts which can be used for future phases. Implement solution in local workstation/notebooks and demo to SME. Iterated and experimented various methods to optimize RAG Pinecone Vector Database PyTorch Keras LSTM and OpenAI Langchain model tuningDesigned Machine learning and statistical models in prepackaged intelligent automation technologies like Langchain Open AI PyTorch BERT built models to enable intelligent document processing and predicting events from historical time series dataDeep healthcare and AI Domain knowledge and expertise within data science, modeling, reporting and analytics – curious about data and have a hacker mindset to continually stay on top of this fast-paced function.
  • Flagship Rtl - Retail Ai For Nike And Ashley Furniture Ai Recommendations
    Senior Data Scientist
    Flagship Rtl - Retail Ai For Nike And Ashley Furniture Ai Recommendations Jun 2022 - Jun 2023
    Designed generative LLM open AI and langchain customer service application that answered questions by creating the vector index of documents and similar chunks of data relevant to the question from the vector representation Used Azure ML OPs Pinecone Langchain OpenAI to find the answer parsed using NLP for Nike Customer Service AI Chatbot and PwC Molina Skin Bot https://www.molinahealthcare.com/ I coded the models for my Recommendation Engine using Open AI and LLM NLP , Collaborative Filtering and Deep Learning algorithms, custom target content feed for each user viewing each media for every location and time and interest. This increased engagement at Nike by 30%.I used NLP BERT Large Language Model and bag-of-words algorithms to first build a dictionary that represents the products and actions that customers engage customers for lead generation and forecasting using Google Analytics to determine customer categories and features . My neural network does feature extraction for the parts of the elements of the data that Nike cared about which then was fed through a data prep pipeline. Optimized Nike supply chains by inventory forecasting with XgBoost in Azure - Microsoft Certified AI Engineer Partnered with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions based on my machine learning expertise. Interact with cross-functional teams to drive data science solutions. I coded the algorithm models and features that customers and internal users leverage to transform the experience and drive efficiencies across the operations of our business.Coded the proprietary algorithm to increase sales and user engagement by 17% for Nike. Used Pinecone Vector Database Langchain Text Embedding and Open AI to build a Chatbot for Taxes and semantic search and customer services automation application document reader for Price Waterhouse Cooper and Molina Healthcare. https://github.com/tmlrnc/LLM
  • Https://Theinfinitereality.Com/ - Ai Llm For Healthcare
    Senior Data Scientist
    Https://Theinfinitereality.Com/ - Ai Llm For Healthcare Mar 2021 - Jun 2022
    I translated raw data into usable and reliable information to unlock decision making, identifying patterns and deliver visibility into model performance and training. I have a 20 year proven track record of successfully solving business problems with innovative and effective machine learning techniques specializing in deep learning neural nets and natural language processing. I know how to remove SPAM and detect and eliminate fraud using artificial intelligence algorithms. Used NLP library spaCy for named entity recognition and part-of-speech tagging. https://github.com/tmlrnc/LLM Used Open AI, Large Language Models, and LangChain to build prompts and indexes for semantic search and customer services automation application document reader and form fillers.Coded Price Waterhouse Gen AI Medical Document Virtual AssistantClassified text NLP data with Naive Bayes, SVM, linear regression, Decision Trees, Random Forest, Nearest Neighbors, XGBoost trees for the optimization of arbitrary loss.I lead an in-house data science team and I designed and coded a deep learning neural net based on python and TensorFlow used for product recommendations, image recognition for image classification, natural language processing, text labeling, video, classification, and meta classification. My recommendation system algorithms then built a custom target content feed for each user viewing based on their historical behavior media for every location and time and interest. My NLP and Deep Learning Recommendation Engine and Artificial Intelligence algorithms increased sales by 30% written by me in Python and SQL and set up using a data pipeline on AWS EC2 and Amazon Sagemaker. I used NLP BERT and bag-of-words algorithms to first build a dictionary that represents the products and actions that customers engage customers for lead generation and forecasting, also coded attention and image recognition using GPT-3 transfer learning and BERT NLP.
  • Grey Jean Technologies
    Senior Data Scientist
    Grey Jean Technologies Feb 2015 - Feb 2021
    New York, Ny, Us
    • Develop abstracted platform services to support applications powered by Generative AIDevelop SDKs and APIs for our user community to power a wide range of applications such as information retrieval, fraud detection, AI Assistants, recommendations on our Gen AI platform.Design and build RAG service platform orchestrations including prompt engineering, guardrails, vector databases, API GroundingBuild out a Prompt management service via cross organizational partnershipsDesigned an Bitcoin price percent movement prediction model using LSTM deep learning neural net trained over 5 years of daily Bitcoin prices and volume, moving averages, stock indexes, interest rates, and Relative Strength Indices for forecasting future Bitcoin prices with 91% accuracy over 7, 20,50, and 200 future day windows.* Created the Curbside Pickup Application and Sold the rights to Walmart Architected and implemented a NLP and Deep Learning predictive analytics recommendation engine that uses proprietary neural nets, natural language processing and data mining models to provide optimal predictions and recommendations that generated 17% increase in online retail sales and 23% increase in new customers FOR WALMART - sold algorithms to the company.Patent for a machine learning algorithm to distribute LSTM neural nets that automatically self-correct and self-learn natural language processing classifiers to solve the given business problem. US Patent GJT-P001-US Decentralized Distributed Machine LearningThe algorithms custom targeted AdTech and Emails and online ecommerce. Increased Walmart online sales by 17% with custom targeted Recommendation Engine based on NLP and Deep Learning in tensorflow and pytorch algorithms that also did top-of-funnel lead scoring applications, enhanced treatment and customer nurture strategies, and other use cases that drive increased conversions and valuable experiences. Working on cloud financial systems.
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  • Flatiron Health
    Lead Data Scientist
    Flatiron Health Oct 2008 - Jan 2015
    New York, New York, Us
    Designed coded built deployed and tuned Machine Learning models in production to accelerate research with the most advanced real-world evidence platform and clinical research technology to enhance data-driven, personalized health care. Simplified and enabled healthcare professionals, managers and business analysts to interpret data and make well-informed decisionsArchitected and built a data driven machine learning platform in TensorFlow, PyTorch, Kera to customize targeted optimization of health care choices and drug research results. Provide hands-on coding, architecture, and leadership to a highly skilled and dedicated engineering team of developers both in house and offshore. Reduced customer churn using Two-Class Boosted Decision Tree and increased customer lifetime value using Boosted Decision Tree Regression. Managed and mentored a team of developers, testers and project managers. Interviewed, recruited, reviewed and grew the technical team. Set my technology department's policies and procedures. Interacted with C-level senior members of other departments and took part in management meetings and setting company direction. Set and manage tech team budget, project timeline, resources roles and responsibilities.Led and mentored a team of researchers in the field of natural language understanding and reasoning, with a focus on healthcare and biomedical applications. Created a domain-specific healthcare knowledge curation framework for machine understanding and advanced clinical decision support systems and tools for complex disease prognosis, diagnosis, and treatment. Utilized knowledge graphs to solve complex AI tasks, such as deep understanding of clinical text and linking diverse biological data
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  • The Orchard
    Senior Data Scientist
    The Orchard Jan 2004 - Oct 2008
    New York, Ny, Us
    • Partnered with product management and engineering teams throughout the product development lifecycle. Achieved the business objectives of the models created in particular robustness, interpretability and implementation cost. Led the understanding and explaining to the team strengths and weaknesses of research papers in ML, algorithmic and optimization. Implemented pragmatic solutions and tested their robustness on data. • Optimizing my Python code, to achieve the same performance of open-source packages such as Numpy or Scikit-learn and integrate your findings in production. • Implementing reliable tests, use continuous integration and exploit at best AWS Cloud capabilities with our back-end engineers.• Solved full stack Data Science problems – Implement solutions to a data science problem in a production environment, coping with all the challenges (such as data cleanliness, performance, unexpected feedback loops, and concept drift) that arise• Mentor junior team members, provide technical leadership and execution guidance• Dive deep into the details when called for while demonstrating good judgement about when to simplify and prioritize. product development. Established engineering best practices (design process/reviews, UML documentation, coding standards, testing standards, information management, deployment processes). Used enterprise-scale agile development methodologies and tools (Eclipse IDE, subversion source control, JIRA, bugzilla, SCRUM, EP, Sprints). Evaluated and managed 3rd party technology vendors and outsourcers. Managed code review, architecture, and planning processes.
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  • Smith Barney - Morgan Stanley
    Senior Software Developer
    Smith Barney - Morgan Stanley Feb 1994 - Jan 2004
    Senior Software Developer that developed Salomon Smith Barney’s online fixed income and equity derivative financial applications and portfolio managers: Build, lead, and mentor a high-performing team of analystsDrive the strategy for product analytics support for multiple product pillarsEnsure the delivery of high quality work by providing technical guidance, implementing standard approaches, and generally providing on-going feedbackPartner closely with Product, Engineering, and Design leadership to drive impact throughout the product development process with research and dataEnsure alignment with partner teams by fostering a collaborative and transparent working modelAdvocate for the team and represent their needs and challenges with cross-functional leadershipPartner closely with our Product leadership team to influence goals, strategy, and product directionWork closely with Research and Analytics leadership to answer important questions about our customers, our product, and the business. www.salomonsmithbarney.com.

Tom Lorenc Skills

Web Applications Agile Methodologies Software Development Scrum Apache Web Services Javascript Mysql Web Development Php Xml Java Cloud Computing Ajax Sdlc E Commerce Databases Oop Enterprise Architecture Linux Soap Java Enterprise Edition Oracle Html 5 Web Architecture Design Patterns Architecture Unix Eclipse Distributed Systems Google Maps Spring Hadoop Web Analytics Websphere Database Design Jsp Object Oriented Design Streaming Media Data Warehousing Administration Digital Video B2b Ecommerce Uml Hibernate System Administration Html5 Machine Learning Object Oriented Programming

Tom Lorenc Education Details

  • Rensselaer Polytechnic Institute
    Rensselaer Polytechnic Institute
    Computer Science
  • Rensselaer Polytechnic Institute
    Rensselaer Polytechnic Institute
    Computer Science
  • Rensselaer Polytechnic Institute
    Rensselaer Polytechnic Institute
    Computer Science

Frequently Asked Questions about Tom Lorenc

What company does Tom Lorenc work for?

Tom Lorenc works for Harmoneyes - Healthcare Ai

What is Tom Lorenc's role at the current company?

Tom Lorenc's current role is Senior Data Scientist.

What is Tom Lorenc's email address?

Tom Lorenc's email address is to****@****dai.com

What is Tom Lorenc's direct phone number?

Tom Lorenc's direct phone number is +164650*****

What schools did Tom Lorenc attend?

Tom Lorenc attended Rensselaer Polytechnic Institute, Rensselaer Polytechnic Institute, Rensselaer Polytechnic Institute.

What are some of Tom Lorenc's interests?

Tom Lorenc has interest in Social Services, Children, Economic Empowerment, Civil Rights And Social Action, Politics, Education, Environment, Science And Technology, Disaster And Humanitarian Relief, Human Rights.

What skills is Tom Lorenc known for?

Tom Lorenc has skills like Web Applications, Agile Methodologies, Software Development, Scrum, Apache, Web Services, Javascript, Mysql, Web Development, Php, Xml, Java.

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