Chad Burris Email and Phone Number

AI assisted stock options trading.Phase I testing using real-life small trades yielded a 262% cash return in one week.Using LSTM and pytorchAutomated hyper-parameterization for daily individual stock fitting.Plan to expand to a generalized automated neural net hyper-parameter fitter for eventual free public release. May help independent decision making when paired with a problem classifier.ML detected insider trading and gave buy signals several times before public announcements. 30-40% accuracy, with 2-4x returns is theoretical profitable but too chaoticPredicted high, low, close and open of SPX with <0.5% average errorUsing python trading bot looking for peaks in MACD and the 26 period EMA of the 14 period RSI as early reversal signals. Combined with buying options day before expiry 1% from the current price and a stop-loss appears to be consistently profitable. Using 36 second candles but believe this should be regularly adjusted to current market conditions (harmonize with the current universal frequency). 66% accurate directionally, researching better direction indicator. 55% profitable trades with outsized upside, researching better trend strength indicator.May use ML, using intraday candles as input or to find best bot parameter settings. May try principle component analysis on top 2-3 dozen indicators. Plan to research how the market changes and automating adjustments.

During this job tenure, I built a comprehensive tool for tracking clinical trial progress across various therapeutic areas, incorporating detailed reporting features. I oversaw all statistical programming tasks related to data anonymization and regulatory disclosure reporting. I engineered code polishing utilities to ensure clean, submission-ready study program code. Additionally, I innovated risk-based data anonymization methodologies and created novel mathematical approaches for quantifying information loss in data anonymization processes.• Improved submission programming for study teams by designing and implementing global SAS macros and tools.• Innovated and developed modified entropy formula for calculating information loss, integrated into an R-Shiny app for optimizing anonymization models.

In this job role, I directed the GRP governance committee to enhance platform development and ensure rigorous qualification standards. I spearheaded the integration of bioinformatics and statistical analysis across diverse therapeutic areas, including oncology and liver disease, leveraging my expertise in Python, R, and JavaScript. I developed automated bioinformatics processes to improve efficiency and accuracy. I led the design and execution of a comprehensive data warehouse to securely house genomic and biomarker data. Additionally, I authored and reviewed procedural documents, ensuring compliance and consistency in clinical bioinformatics.• Introduced inclusion of genetic data in CSR at Gilead by conducting genomic analysis and authoring genomic analysis reports.• Initiated modeling techniques for subject enrollment projections by utilizing python, AWS, Snowflake, and Matillion, drawing from variety of data sources.

In these positions, I headed a diverse team of 12 statistical programmers, ensuring efficient allocation of resources across various biomarker projects. I contributed to cross-departmental standardization efforts by fostering collaboration and integrating best practices. I also steered the training and professional development of team members, promoting skill enhancement and career progression.• Streamlined biomarker statistical programming processes to improve operational efficiency and practices companywide.• Led development and implementation of CDISC compliant ADaM and SDTM specifications for enhancing data consistency and regulatory compliance.

In this job role, I developed ADaM and SDTM compliant datasets, ensuring adherence to industry standards for clinical trial data. I authored detailed dataset programming instructions to enhance team efficiency and accuracy. Engaging in interdisciplinary meetings, I facilitated cross-departmental collaboration. I optimized workflow and project delivery by assigning programming tasks to team members. Additionally, I mentored and guided junior programmers, cultivating their skill development and problem-solving capabilities.• Spearheaded programming initiatives by overseeing teams of 3-5 programmers to deliver high-quality statistical reports.• Acted pivotal role in stat QC of primary efficacy endpoints by collaborating closely with statisticians for accurate analysis.

In this job role. I developed ADaM and SDTM compliant datasets, ensuring adherence to industry standards for clinical trial data. I authored detailed dataset programming instructions to enhance team efficiency and accuracy. Engaging in interdisciplinary meetings, I facilitated cross-departmental collaboration. I optimized workflow and project delivery by assigning programming tasks to team members. Additionally, I mentored and guided junior programmers, cultivating their skill development and problem-solving capabilities.• Spearheaded programming initiatives by overseeing teams of 3-5 programmers to deliver high-quality statistical reports.• Acted pivotal role in stat QC of primary efficacy endpoints by collaborating closely with statisticians for accurate analysis.