
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 firm specializing in data, full-stack development, and AI solutions through project-based contracts and consulting engagements. Premier Analytics focuses on open-source programming, big data workflows, AI/ML/DL engineering, full-stack development, and statistical modeling for clients across private industry, research, and government sectors.
Ryan has extensive experience delivering technical solutions across a range of roles, including consultant, big data scientist, full-stack developer, AI engineer, and statistician. His expertise includes Python, R, SAS®, JavaScript (Vite, React.js, Node.js), SQL, and applied AI frameworks, including machine learning and deep learning libraries. He has been involved in client contracts, technical consulting assignments, funded research projects, and interdisciplinary initiatives, bringing a results-driven approach to every engagement.
Ryan holds a Master of Science in Big Data Analytics (2023) and a Bachelor of Science in Statistics with a Minor in Quantitative Economics (2020), both from San Diego State University (SDSU). He also serves as an Adjunct Faculty member for SDSU’s Big Data Analytics Graduate Program and the Department of Mathematics and Statistics. His professional interests include applied AI, DevOps and MLOps, open-source software, full-stack architecture, statistical modeling, and scalable data infrastructure.
Email: rplafler@premier-analytics.com
LinkedIn: www.LinkedIn.com/in/RyanPaulLafler
Website: www.Premier-Analytics.com
Making Organization's Data Dreams into Data Realities
From developing data-driven full-stack applications leveraging big data in the cloud and on private servers to training, optimizing, and deploying machine learning workflows for organization's AI needs, Ryan's experience using Python, R, SAS, JavaScript, open-source APIs, and databases (SQL, file storage providers, cloud storage providers, NoSQL, and document-based) gives him the versatility to manage and help organization's develop all aspects of their data-oriented processes.
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 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 programming, R programming, AI/ML/DL, statistical analysis, GIS analysis, database structuring, and application development to immerse students in applied fields of study.
Fall 2023: Advanced Special Topics in Big Data Analytics (BDA 696)
Spring 2024: Machine Learning Engineering (BDA 602) and Spatiotemporal Analysis and Modeling (STAT 596)
Fall 2024: Advanced Special Topics in Big Data Analytics (BDA 696) and Applied Multivariate Statistics (STAT 520)
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.
Instructor and Graduate Teaching Associate
Aug 2021 - May 2023
Department of Mathematics and Statistics, San Diego State University
Instructor 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. | 3.88 GPA
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. | 3.77 GPA
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.