Kevin Lee Email & Phone Number
@cornell.edu
5 phones found area 610, 650, and 925
LinkedIn matched
Who is Kevin Lee? Overview
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Kevin Lee is listed as Chief Technology Officer at Clinvia, a with 14 employees, based in Greater Philadelphia, United States. AeroLeads shows a work email signal at cornell.edu, phone signal with area code 610, 650, 925, and a matched LinkedIn profile for Kevin Lee.
Kevin Lee previously worked as Senior Director of Biometrics & Data Science at Bristol Myers Squibb and Machine Learning Course Instructor at Cornell University. Kevin Lee holds Bse, Chemical Engineering from University Of Pennsylvania.
Email format at Clinvia
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About Kevin Lee
I'm a passionate data scientist with a proven track record of leveraging Data and Advanced Analytics to solve complex business challenges and drive innovation. I have extensive experience in areas like:- Data Science : Data Science, Machine Learning, Deep Learning, Transfer Learning, MLOPs, NLP- Gen AI : LLM, Gen AI, ChatGPT, Gemini, Copilot, LangChain, Agents, RAG, Vector DB, fine-tuning- Prompt Engineering : Zero-Shot, Few-Shot, Chain of Thoughts- Biometrics : Clinical Trials, Phase 1 to 4, Protocol, Sample Size, SAP, EDC, CDISC, TFL, FDA Submission- SAS, Open source programs (Python, R, SQL), Tableau, Atleryx, Power BI- CDISC : CDASH, SDTM, ADaM, Standards-driven MDR, End to End Standards driven Clinical Trials- Oncology expert : RECIST, Cheson, IWCLL, SDTM (TU, TR, RS), ADaM, Time-to-Event Analysis- Commercial Analytics : Sales growth, Optimizing ROI, New Market opportunities and trends using NPA, LAAD, Xponent, Digital, Payer Data- Regulatory Submission : SDTM and ADaM data packages- Data Experience: IQVIA LAAD, NPA, Xponent, Veeva, Provider, Specialty Pharma, Diagnosis, Therapy, Digital, Call Plan, RWE, EHR, CDISC, HL7 Throughout my career, I've actively shared my knowledge by presenting at conferences (> 100 papers) and teaching courses on Machine Learning, Generative AI, Python Programming, Oncology, CDISC standards, and submission. I believe in continuous learning and strive to stay at the forefront of the ever-evolving data science and AI landscape.Disclaimer : My postings reflect my own views and do not necessarily represent the views of my employers.
Listed skills include Sas, Cdisc, Clinical Trials, Data Management, and 10 others.
Kevin Lee's current company
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Kevin Lee work experience
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Senior Director Of Biometrics & Data Science
Current- Build and Lead a High-Performing and Innovating Clinical Trial Systems & Advanced Analytics Team by Fostering a Culture of Empowered Collaboration, Open Communication, Continuous Learning, Challenging the Status Quo and Leading by Example.- Lead the Implementation of a Clinical Trial Data Repository & Advanced Analytics Systems and Processes, Streamlining Data Collection and Analysis for Improved Clinical Trial Efficiency.- Lead Real-Time Clinical Trial Dashboard to Improve Patient Enrollment, Recruitment, Operational Efficiency & Cost Saving and to Enhance Patient Data Analysis, Safety Monitoring, and Decision Making.- Champion Innovation, Optimization and Efficiency by Leading Open-Source Programming, Data Science, and Generative AI Projects
Machine Learning Course Instructor
Current- Problem Solving with Machine Learning- Estimating Probability Distribution- Learning with Linear Classifiers- Decision Trees and Model Selection- Debugging and Improving Machine Learning Models- Learning with Kernel Machines- Deep Learning and Neural Networks
Ai Strategy Course Instructor
Current- Introduction of AI- Knowledge-Based AI Technologies- Machine Learning and Data-Based Approaches to AI- Strategic Implementation of AI Systems- Societal Impacts of AI- Future of AI
Generative Ai / Chatgtp Instructor
Current- Introduction of LLM, Gen AI and ChatGPT- ChatGPT Use Cases - Prompt it, not Google it- Prompt Engineering- Gen AI tools (e.g., ChatGPT, Copilot, Gemini)- Gen AI API in SAS, Python, R- LangChain, RAG- Gen AI (e.g., ChatGPT) Risk and Concerns- Gen AI (e.g., ChatGPT) Implementation Roadmap- Future of Gen AI/ChatGPT
Python Programming/ Machine Learning Training Instructor
Current• Introduce Python programming and Jupyter notebook• Teach Python basic data types – String, Number, List, Dictionary, Array and Date Frame.• Teach how to read and write files (txt, csv, xls, SAS, image)• Teach how to wrangle and manipulate data – sorting, merging, filtering and transposing. • Teach feature engineering and visualization • Teach Machine Learning programming in DNN, CNN and RNN using Numpy, Pandas, Keras, Tensorflow, sklearn
Oncology Clinical Trial Study Training Instructor
Current- Introduce Oncology Studies and its types - Solid Tumor, Lymphoma, Leukemia, Immunotherapy- Teach concepts and guidelines of Response Criteria (RECIST, irRC, Cheson, IWCLL)- Teach how to collect, measure and determine tumor responses based on Response Criteria. - Teach Ocology-specific CDISC Standards (SDTM, ADaM, CT) - Teach Oncology-specific Analysis (ORR, OS, PFS, Kaplan Meier Curve)- Demonstrate End to End Standards-driven automated Oncology Studies
Director Of Data Innovation
- Lead Clinical Development Innovation using Cloud Computing, Data Science, Advanced Analytics, Data Warehouse, AI, LLM & Gen AI.- Lead the implementation of a real-time Clinical Operation and Trial data review platform for a 20% reduction in review & analysis time.- Develop and validate a compliant data review and analytics system, ensuring adherence to Regulatory guidelines(ICH, GxP, CFR, GDPR).- Lead an exploratory analysis to reduce sample size using Gen AI.- Develop and implement AI, LLM & Gen AI strategies - Risk Assessment, Use Case exploration, Policy development, education, PoC & ROI justification.- Collaborate with RWD team for patient recruitment, study design and control arm.- Lead OpenAI ChatGPT and MS Copilot implementation for enhanced data analysis and content generation to increase 15% productivity increase. - Lead department infrastructure projects (SOP development, Data Migration, Sample Size Calculation Reduction, System Integration and Validation).
Assistant Vice President Of Data Science And Machine Learning
- Deliver Machine Learning (ML) / Data Science products/services. - Transform SAS Programming department (+150 SAS programmers) to Data Science team by integrating Cloud computing environment (AWS Redshift, S3, EC2) and Opensource analytics system (R Studio / Jupyter).- Provide actionable business intelligence with Tableau, R, Python and SQL Open-source programming using RWE data (e.g., Claim, LAAD, Payer, EHR) - Influence Senior Leadership on business opportunities with RWE. - Provide RWE thought leadership by designing analysis design, developing methodology, and leading the technical expertise in Advanced Analytics. - Lead Big Data & Data Science Strategy, Process and Governance for organizational initiatives. - Build and lead Data Science team of data scientists, data engineers and machine learning engineers to build cutting-edge ML and DS technologies.- Develop and lead MLOPs – business requirements, data preparation, ML model training, validation, deployment, & continuous learning. - Mange and monitor AWS environments - S3, EC2 Instances, EBS, EFS, EMR, ECS, RedShift
Machine Learning Seminar Instructor At Sas Global Forum
Teach Machine Learning Course at Pre-conference Tutorial
Director Of Data Science
- Worked with clients to support the drug development life cycles, including CDISC implementation, MDR implementation, SAS programming, statistical analysis, and electronic submission to FDA.- Helped clients on their biometrics department infrastructure, outsourcing strategies, data analysis, regulatory support and training. - Analyzed information (e.g., current standards implementation, drug development process and business workflows) and performed risk assessment and gap analysis for regulatory compliance. - Provide end to end biometric support from Protocol, SAP, EDC, SDTM, ADaM, TFL, SDRG, ADRG, Define.xml, CSR to Submission- Consult with clients to develop and implement innovative technologies such as data-driven process and Machine Learning implementation. - Supported clients on machine learning implementation - data pipelines, feature engineering, model building/training (regression, classification, DNN, CNN, RNN, NLP, Transfer Learning) and deployment. - Located and developed new business by coordinating business requirements, developing and negotiating contracts, and closing contracts. - Responded to RFI and RFP and presented business proposals and solutions to clients.
Solution Architect / Technical Sales Engineer
- Provided a high level of technical expertise (e.g., NoSQL database) and enterprise architecture integrations.- Conducted detailed customer requirement gathering, discovery and analysis.- Worked closely with customers in the architectural design and implementation or integration of data-driven projects.- Proposed and designed technical solutions which included creative prototypes and proof of concept. - Built and gave customer-specific demonstrations leveraging NoSQL enterprise database system. - Acted as an interface between Sales organization and technical staff for production management. - Collaborated effectively with both the Business and Technical team to provide clients with possible solutions to their issues and problems. - Accompanied sales teams on prospect/customer visits.- Responded to functional and technical elements of RFI and RFP.- Represented the products and company to customers at filed events (e.g., conferences).- Conveyed customer requirements and feedbacks to Product Management teams. - Provided technical consulting, strategic post-sales or systems-integration consulting, technical business development and simple programming in XQuery, SPARQL and SOAP/REST API.- Loaded structured, unstructured data (XML and JSON), triples and ontologies (RDF and OWL) on NoSQL database to show how data could be easily integrated and searchable. - Provided technical experiences on search engines, Hadoop integration, NoSQL databases, AWS integration, ETL tools, geospatial systems, semantic technology, knowledge-management systems and content-management systems.
Senior Clinical Data Scientist Consultant
Worked with clients to support the system change, process change and software implementation. Interviewed or facilitated focused group discussion with stakeholders, managers, and other employees for data, information and documents gathering.Checked and analyzed information such as current standards implementation, metadata management, governance, business flows, and other relevant data.Identified issues, formed hypotheses and solutions and presented findings and recommendations to clientsPerformed risk assessment and gap analysis of client’s current state and future, desirable but obtainable state of solutions. Provided solutions and strategies to clients using Software as a Service(SaaS), mainly Metadata Repository(MDR). Helped clients to process the successful software development life cycle – Plan, Analysis(e.g., URS and FRS), Design (e.g., Design Specification), Development, Validation(e.g., UT, IT, and UAT) and Implementation. Helped to build the conceptual data model, logical data model and physical data model for SaaS. Helped software development team to develop the client’s specific customized SaaS.Developed the new technologies(e.g., system integration over web services, semantic technology, metadata-driven business process) and new strategies(e.g., Standards Capability Maturity model) to help the company exposure in industry.Built the integration between SaaS and analytic system (i.e., SAS) using web service technology. Developed the client’s specific metadata repository to help data-driven clinical data development life cycle. Supported business development through the RFP and sales processKept abreast of industry trends in data management, data analysis, data warehousing, and data(e.g., CDISC) standards. Consulted clients on CDISC Strategic Roadmap. Consulted clients on Standard Governance Design (i.e., organization, process and technology).Supported Semantic Technology(e.g., RDF, OWL, RDFS, SPARQL)
Statistician/Cdisc Lead/Program Lead
Built and led the collaborative partnership with the clients. Led successful CDISC projects fully utilizing offshore programmers/statisticians. Prepared NDA/IND Electronic submission to FDA in CDISC format. Built a successful team and led the team to successful projects.
Manager/Clinical Trial Statistical Programmer
Managed SAS Department by managing projects, timelines and human resources
Principal Clinical Trial Sas Programmer
Lead the SAS programming side of the clinical trial by providing the SAS programming support to Data Manager, Oracle Clinical Programmer, Statistician, Medical Writer and Quality Assurance.
Clinical Data Management Sas Programmer
Provided SAS programming support to clinical trial data managment.
Sas Programmer
Kevin Lee education
Bse, Chemical Engineering
Ms, Applied Statistics
Frequently asked questions about Kevin Lee
Quick answers generated from the profile data available on this page.
What company does Kevin Lee work for?
Kevin Lee works for Clinvia.
What is Kevin Lee's role at Clinvia?
Kevin Lee is listed as Chief Technology Officer at Clinvia.
What is Kevin Lee's email address?
AeroLeads has found 1 work email signal at @cornell.edu for Kevin Lee at Clinvia.
What is Kevin Lee's phone number?
AeroLeads has found 5 phone signal(s) with area code 610, 650, 925 for Kevin Lee at Clinvia.
Where is Kevin Lee based?
Kevin Lee is based in Greater Philadelphia, United States while working with Clinvia.
What companies has Kevin Lee worked for?
Kevin Lee has worked for Clinvia, Bristol Myers Squibb, Cornell University, Pharmasug, and Karuna Therapeutics.
How can I contact Kevin Lee?
You can use AeroLeads to view verified contact signals for Kevin Lee at Clinvia, including work email, phone, and LinkedIn data when available.
What schools did Kevin Lee attend?
Kevin Lee holds Bse, Chemical Engineering from University Of Pennsylvania.
What skills is Kevin Lee known for?
Kevin Lee is listed with skills including Sas, Cdisc, Clinical Trials, Data Management, Clinical Data Management, Statistics, Data Analysis, and Sas Programming.
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