
Ryan Paul Lafler, M.Sc.
President, CEO, and Lead Consultant
Ryan Paul Lafler is the President, CEO, and Lead Consultant of Premier Analytics Consulting, LLC, a San Diego–based consulting firm specializing in AI & ML systems, big data engineering, statistical analysis, and custom full-stack analytics platforms. He works closely with enterprise organizations, public-sector agencies, and research institutions to help teams process, analyze, and work with their complex data in support of informed decision-making.
Ryan brings hands-on experience as a consultant, full-stack developer, AI & ML engineer, and data scientist. His work centers on data-driven full-stack platforms; big data infrastructure; statistical analysis and modeling; and building fine-tuned AI & ML systems with a strong emphasis on localization, reliability, validation, and long-term maintainability.
Ryan's technical expertise spans analytics and AI development using Python, R, SQL and NoSQL systems, SAS®, and modern JavaScript frameworks, supporting solutions that integrate data engineering, analytics, visualization, and AI systems into cohesive platforms.
In addition to running Premier Analytics Consulting, Ryan serves as contracted Adjunct Faculty at San Diego State University for the Big Data Analytics Graduate Program, contributing applied instruction informed by real-world analytics, data, and AI implementation. He earned his Master of Science in Big Data Analytics (2023) following the successful defense and publication of his thesis, and his Bachelor of Science in Statistics with a Minor in Quantitative Economics, with Distinction (2020), both from San Diego State University.
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Turning Your AI, Data, and Full-Stack Visions into Intelligent Systems
Learn more about Ryan's AI & ML, analytics, and full-stack development leadership
Ryan Paul Lafler leads analytics and AI initiatives that help organizations move from complex data and exploratory ideas to systems that function reliably in real-world environments. His work focuses on applied artificial intelligence and machine learning (AI/ML), statistical analysis, big data engineering, and custom full-stack analytics platforms built to support real decision-making.
In addition to consulting and contract work, Ryan regularly leads training engagements and technical workshops for professional, academic, and industry audiences. These engagements emphasize applied methods, validated workflows, and practical implementation, helping teams build internal capability alongside delivered systems.
Ryan maintains an active commitment to knowledge sharing through conference presentations, workshops, and published technical materials. He regularly contributes to professional and academic conferences, sharing lessons learned from real projects, applied AI systems, and modern analytics workflows to support broader learning and adoption across the analytics community.
Through Premier Analytics Consulting, Ryan and his team partner with enterprise, public-sector, and research organizations to design, build, modernize, and teach analytics systems with an emphasis on clarity, validation, and long-term reliability.
Professional Experience
President, CEO, and Lead Consultant
Aug 2023 - Present
Premier Analytics Consulting, LLC
President, CEO, and Lead Consultant for Premier Analytics Consulting, LLC. Manage contracts, project-based assignments, and client relationships. Involved in each of our Clients' projects. Deliver training and hands-on-workshops at professional data science conferences across the United States.
Well-Versed in Open-Source Programming Languages and Proprietary Programming Languages
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Well-versed in Open-Source languages including Python, R, JavaScript frameworks (Vite, React.js, Node.js), and SQL
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Experience in proprietary languages and products including SAS, Google Earth Engine, and ArcGIS
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Develop responsive applications with scalable API frameworks (FastAPI and Node.js)
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Create full-stack applications and conduct analysis in programming languages tailored to Clients' needs
Experienced in Data Engineering, Data Pipeline Development, and Data Processing
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Engineer high-speed pipelines into cloud storage services such as Amazon S3 and Google Cloud Storage
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Process unstructured images, videos, audio files, and text sources as inputs for models and algorithms
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Query data inside of structured relational databases and import semi-structured delimited files
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Experienced in spatiotemporal data formats, file types, tiling providers, and storage services
Implementing Scalable, Data-Driven Analysis using Python, R, and SAS
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Assist Clients develop optimized workflows that scale well for big data in Python, R, and SAS
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Perform programming language conversions between Python, R, and SAS
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Develop training seminars and hands-on-workshops for Python, R, and SAS users
Developing Responsive and Interactive Full-Stack Systems & Web Apps
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Experienced in React.js for developing sleek and professional front-end interfaces
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Integrate server-side data analysis, requests, and data querying using Python's API frameworks
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Create interactive web applications and dashboards that are tailored to Clients' needs
Adjunct Faculty
Aug 2023 - Present
Big Data Analytics Graduate Program, San Diego State University
Part-Time Faculty. Responsible for designing and delivering curriculum for certain graduate-level courses in the Big Data Analytics Program, Department of Mathematics and Statistics, and Global Campus Program at San Diego State University. Responsibilities include building courses that teach practical, industry-expected skills in data science, presenting engaging lectures, and selecting topics from several areas in data science ranging from Python, R, & SAS programming, AI/ML/DL frameworks and workflows, statistical analysis, GIS analysis, database structuring, and application development to immerse students in applied fields of study.
Fall 2025: Advanced Special Topics in Big Data Analytics (BDA 696), Applied Multivariate Analysis (STAT 520), Machine Learning Engineering (BDA 602)
Spring 2025: Machine Learning Engineering (BDA 602), Spatiotemporal Analysis and Modeling (STAT 596)
Fall 2024: Advanced Special Topics in Big Data Analytics (BDA 696), Applied Multivariate Analysis (STAT 520)
Spring 2024: Machine Learning Engineering (BDA 602), Spatiotemporal Analysis and Modeling (STAT 596)
Fall 2023: Advanced Special Topics in Big Data Analytics (BDA 696)
Data Scientist and Researcher
Aug 2019 - May 2023
Climate Informatics Laboratory, San Diego State University
Oversaw and coordinated research into the development of supervised and generative neural networks (deep learning models) for unstructured image and video data. Particular emphasis on visualizing spatial data that changes over time (spatiotemporal data) using Python, R, and Google Earth Engine. Designed interactive applications with front-end interfaces for viewing, querying, and analyzing climatological, geological, and environmental data.
Implemented relational databases for efficiently storing and querying downloaded climate image data, giving structure to unstructured datasets through SQL integrations in Python for GIS analysis. Designed data pipelines to optimize loading of Big Data into models for training and prediction. Processed historical and real-time Big Data from NOAA, EMCWF, CMIP6, the U.S. Census Bureau, and Google Earth Engine for visualization, analysis, and modeling.
Developed a series of R statistical programming videos for reporting descriptive statistics, visualizations, and performing array operations taking advantage of R's vectorization and built-in functions. Training videos are posted publicly on YouTube, viewable by clicking here.
Graduate Teaching Associate
Aug 2021 - May 2023
Department of Mathematics and Statistics, San Diego State University
Graduate Teaching Associate at San Diego State University for Introductory Statistics: STAT-250. Trained students in using Microsoft Excel for data extraction, cleaning, exploratory analysis, visualizing variables, building linear regression models, conducting parametric statistical tests to evaluate claims, and drawing conclusions from results. Discussed the assumptions and limitations of popular parametric tests and regression models, including when to use certain statistical tests over others.
Developed presentations and hands-on activities to engage students in weekly lectures. Received overwhelmingly positive anonymous reviews from students, available upon request.
Academic Profile
Successfully defended and published a Thesis on "Video Remastering" in Python that introduces methods for doubling any video's framerate, enhancing its resolution, and generating statistically-valid baseline metrics for evaluation with similar upsampling models. Completed several projects focusing on model-making and relational database structuring for business analytics, climatology, political science, and other fields. Concentrated on programmatic data analysis using languages including Python, R, SAS, and SQL.
Master of Science in Big Data Analytics, M.Sc.
Jan 2021 - May 2023
Big Data Analytics Program, San Diego State University
Published a Thesis that was approved by a Committee of distinguished professors from the Big Data Analytics Program and the Department of Mathematics and Statistics. Completed projects, conducted research, developed products, and fulfilled coursework involving topics about:
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Machine Learning (Ensemble Methods, Random Forest, Gradient Boosting, SVM),
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Deep Learning Architectures,
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Statistical Analysis (Hypothesis Testing, Multiple Linear Regression, Logistic Regression, Generalized Linear Models),
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Time Series Analysis & Spatiotemporal Analysis,
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Relational Database Development, Querying, & Management,
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Consulting Projects,
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Climate Informatics and Data Visualization.
Extensive programming in Python, R, SQL, and SAS for data analysis tasks. Research included developing neural networks through TensorFlow in Python, evaluating machine learning algorithms for classification, regression, segmentation, and dimensionality reduction, and conducting spatiotemporal analysis on climatology data.
Bachelor of Science in Statistics, B.Sc.
Minored in Quantitative Economics
Aug 2017 - Dec 2020
Department of Mathematics and Statistics, San Diego State University
Graduated Magna cum Laude with Great Distinction in Statistics. Recipient of Dean's List in 2017, 2018, 2019, and 2020.
Awarded the Academic Excellence in Statistics honor from the Department of Mathematics and Statistics.






















