Nathan Madlansacay
Data Reporting & Analyst Specialist, @ Pacific Psychiatry, Inc.
About
AI and machine learning enthusiast with a strong ambition to become a data analyst or data scientist, open to applying analytical skills across diverse industries. Skilled in leveraging Python, statistical methods, and machine learning algorithms to extract insights, build predictive models, and solve complex problems. I am eager to learn new technologies, expand my expertise, and contribute innovative solutions that drive data-informed decision-making.
United States
Oakland
Information Technology & Services
Electronic Medical Record (EMR), Data Analytics, Pandas (Software), Machine Learning, Commercial Real Estate Analysis, Database Tools, Data Science, Mathematical Statistics, Base SAS Certified, Cardiopulmonary Resuscitation (CPR), Causal Analysis, Bayesian statistics, Programming Languages, Predictive Modeling, Computational Mathematics, Analytical Techniques, Machine Learning Algorithms, Traffic Analysis, Data-driven Decision Making, Cluster Analysis
Experience

Data Reporting & Analyst Specialist,
San Luis Obispo County, CA
In this psychiatry role, I supported clinical and administrative operations with a strong focus on scheduling efficiency and patient access to care. I worked closely with appointment systems to manage provider calendars, monitor scheduling density, and reduce bottlenecks that could delay treatment. Through this work, I saw firsthand how overly dense schedules can limit meaningful patient-provider interaction, increase clinician fatigue, and negatively impact continuity of care, while underutilized schedules can reduce access for patients in need. By analyzing appointment patterns, no-show rates, and visit durations, I helped identify opportunities to better balance workload and ensure patients received timely, effective psychiatric treatment. This experience strengthened my understanding of how operational decisions directly influence clinical outcomes in mental health settings.
Education

Cross Disciplinary Studies Minor in Data Science
Through an inter‐college collaboration, the Computer Science and Statistics departments offer a cross‐disciplinary minor in Data Science — a rapidly evolving discipline that uses elements of statistics and computer science to gather, organize, summarize, and communicate information from a variety of data sources and data types. Job opportunities for data scientists are growing as the availability of data becomes ever abundant via the internet, consumer transactions, sensor arrays, medical records, embedded biometrics, bionformatics, etc.
Statistics
Data Science
Nathan Madlansacay's Contact Information
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