Richard W. St. Germaine, Ph.D, MPH, CFA

LinkedIn: https://www.linkedin.com/in/richard-st-germaine-phd-a62642182/

GitHub: https://www.github.com/stger040

EDUCATION:

University of Minnesota – Ph.D. Statistics Major, 2023

University of Minnesota – Master’s of Public Health, Biostatistics Major, 2021

University of Minnesota – Bachelor’s of Science, Biochemistry Major, 2019

CERTIFICATION:

Active FINRA Series 7: General Securities Representative Examination

Active FINRA Series 65: Uniform Investment Advisor Law Examination

Active FINRA Series 63: Uniform Securities Agent State Law Examination

Google Professional IT Python Programmer by Google Certification Program #A5820VG, Iss: July 2022

Google Data Analytics (R programming) by Google Certification Program #A5820VG, Iss: Aug 2022

Amazon AWS Certified Data Analytics-Specialty by Amazon AWS #417289, Iss: Sept 2021

SAS Certified Data Scientist using SAS 9 by SAS Global Certification Program #94027111, Iss: Aug 2021

SAS Certified Clinical Trials Programmer using SAS 9 by SAS Global Certification Program #94027111, Iss: Jan 2021

CONTRACT CONSULTING:

Quantitative Trader – St. Germaine Capital LLC – Minneapolis, MN – May, 2018 to present

Designed, developed, and implemented quantitative trading strategies.

Managed the investment portfolios of two tribal entities, tailoring investment strategies to meet their unique financial goals and risk tolerance levels.

Provided individual portfolio management services for 11 tribal members, developing personalized investment strategies to optimize returns and minimize risk.

Leveraged Google Cloud Platform (GCP) to host a proprietary trading platform, enhancing computational efficiency and scalability for real-time market analysis and trade execution.

Utilized advanced machine learning and deep learning techniques to predict market movements, identify trading opportunities, and execute trades all with Python programming.

Employed GCP’s robust infrastructure for backtesting algorithms and securely managing vast datasets, ensuring optimal trading strategy performance and data integrity.

Continually monitored financial markets and adjusted trading strategies as needed to respond to market trends and economic events.

Managed all aspects of trading operations, including compliance, risk management, and coordination with brokerage and data service providers.

Produced regular reports for all clients detailing portfolio performance, trading activity, and market analysis.

Maintained open lines of communication with all clients, providing updates on their investments and addressing any questions or concerns they had.

Ensured full compliance with all applicable financial regulations and maintained meticulous records of all trading activity.

Data Scientist Consultant – St. Germaine Data Innovations LLC – Minneapolis, MN – May, 2019 to present

Founded a data firm specializing in applying advanced AI methodologies to address common data issues that impede tribal research using quantitative research methods.

Implemented indigenous data sovereignty measures to help tribes regain control over their data, recognizing the cultural, ethical, and legal implications of indigenous data rights.

Utilized GCP or AWS to establish secure, scalable data warehouses for tribal clients, supporting indigenous data sovereignty practices through enhanced control and accessibility of data.

Developed data pipelines on GCP and AWS (whichever tribal IT departments were currently using at the time), integrating tribal data sources into centralized systems for advanced analytics (ETL methods), while adhering to strict data sovereignty and security protocols.

Leveraged Apache Spark and R programming to process and analyze massive datasets, delivering faster and more efficient data processing for tribal clients.

Developed Spark-based data transformation and analysis pipelines, improving the scalability and performance of data processing workflows.

Employed Spark's machine learning libraries for advanced predictive modeling, enhancing decision-making capabilities for tribal leaders.

Assembled and led teams of data professionals, including data engineers, data scientists, and data analysts/epidemiologists/business intelligence analysts, based on departmental needs and objectives.

Developed and installed MySQL servers on onsite tribal servers to facilitate direct and secure data access.

Programmed API connections to existing data sources, enabling tribes to have full access to their raw data while ensuring data security and sovereignty.

Consulted with tribal leaders and stakeholders to understand their unique data challenges, proposing AI-powered solutions tailored to their needs.

Designed and implemented machine learning models and algorithms in R to extract insights from complex datasets, improving decision-making and strategic planning.

Developed comprehensive data management and governance strategies, ensuring data quality and integrity while respecting tribal data sovereignty principles.

Provided training and technical support to tribal data teams, empowering them to manage and analyze their own data effectively.

Produced detailed reports and presentations to communicate findings and data-driven recommendations to tribal leaders and stakeholders.

Senior Data Scientist (contract) – Corteva Agriscience – Woodbury, MN – January, 2023 to June, 2023

Worked closely with cross-functional teams to understand business requirements and develop data-driven solutions that drive business value.

Collected and analyzed large, complex datasets to extract valuable insights that inform business decisions and drive innovation.

Leveraged Apache Spark and R programming to process and analyze vast agricultural datasets, significantly improving data processing speed and efficiency.

Developed Spark-based machine learning models to predict crop yields and optimize agricultural operations, contributing to data-driven decision-making in the agricultural industry.

Designed, developed, and implemented machine learning models and algorithms to solve complex business problems.

Developed and maintained predictive models, data visualizations, and other analytical tools to enable decision making and communicate insights to stakeholders.

Collaborated with other data scientists, engineers, and software developers to build scalable, efficient, and reliable data pipelines and infrastructure.

Stayed up-to-date with the latest developments in data science, machine learning, and artificial intelligence and apply these developments to improve our solutions and processes.

Senior Biostatistician (contract) - ProPharma Group - Minneapolis, MN - August, 2022 to February, 2023

Efficiently and effectively executed statistical activities for multiple projects simultaneously.

Assisted in the development of statistical analysis plans (SAPs), clinical study reports (CSR), and other relevant biostatistics activities.

Interacted with project team, as well as key internal and external stakeholders.

Supported programming of, and/or reviewed statistical tables, listings, figures, and analysis of (real-world data from sponsor’s EDCs) datasets for clinical trials in accordance with ProPharma Group or a client's Standard Operating Procedures (SOPs) or study specific guidelines.

Maintained awareness of project tasks and effectively communicate the status of such tasks to other members of the ProPharma Group team as requested.

Supported programming in SAS and/or R to create output as needed by sponsors, including presentation-ready tables, listings, and figures.

Performed other responsibilities as required

Clinical Biostatistician – Endologix - Irvine, CA – August, 2021 to August, 2022

Reviewed and drafted Statistical Analysis Plans (SAPs) and developed R programming solutions for analysis of clinical data.

Led two retrospective cardiovascular medical device studies requested by FDA, determined study limitations by literature review for sample size, power, methods, table shells, and novel approach.

Determined sample sizes for new studies and appropriate statistical methodology

Assisted in statistical model selection, experimental design, design and analysis of clinical trials

Analyzed and interpreted data from individual trials

Perform meta-analyses by pooling data from several studies

Initiated, plan, executed and managed all aspects of data analysis/management such as case report form design, defined/program database/edited check specifications, assisted in mid-study updates (MSU), contributed to the creation and maintenance of databases

Analyzed clinical datasets within the R programming server (R Studio, aka Posit Cloud) and present results in a comprehensive and intuitive fashion to regulatory, clinical, and marketing audiences. Provided deliverables (tables/listings/graphs and interpretations) with an emphasis on quality and clarity for all regulatory submissions

Collaborated with R&D team for analysis and design of experiments for stent design and tolerances, polymer chemistry formulation and performance

Clinical Data Scientist – Medtronic - Minneapolis, MN – August, 2020 to January, 2022

Developed time-series machine learning models (ARIMA, SARIMA, and LSTM) to train on, test, and evaluate predictions of averages of T-waves in EKG data of 9000 two minute files. Machine learning models were created in R programming.

Provided clear and organized written procedures to support workflow process, query design, etc to allow replication of work of EKG data

Developed reports and analyze data to measure clinical outcomes, network performance and methodology levers on EKG data with T-wave analysis

Created and maintains high quality documents, and adheres to quality standards set by management

Responsible for executing statistical analysis plans created by the statistician and/or QSV team managers

Data Science Intern – University of Minnesota Twin Cities - Minneapolis, MN – August, 2020 to May, 2021

Demonstrated professional ability and motivation by acting as the biostatistician and participated in analysis in the data core and being responsible from study design to early stage oncology clinical trials

Wrote methods and results sections of six manuscripts published in peer-reviewed scientific journals, featuring both analysis results and statistical methodology.

Implemented python scripts for data cleaning automation to allow for effective statistical analysis on large clinical datasets.

Through R programming, conducted sample size calculation. Prepared statistical analysis plans. Carried out data cleaning and manipulation. Conducted data analysis of clinical, laboratory, surveys and device measured data applying standard and non-standard statistical methodology from exploratory analysis to final model building, sensitivity analysis, diagnosis, necessary post-hoc subgroup analysis.

Developed advanced programming and statistical skills through extensive on-the-job use.

Educated team members without statistical background with basic statistical method and programming.

Biostatistics Graduate Teacher – University of Minnesota – Minneapolis, MN – September, 2019 to May, 2020

Primary instructor for PUBH 7462 Biostatistics in R programming (Fall ’19 and Spring ’20), advised by previous instructor Dr. Haitao Chu.

Responsibilities include grading, holding office hours, and teaching a weekly instruction session.

Worked individually with students to enhance the understanding and application of core course concepts with the goal of success in the classroom and beyond.

Tutor, Advanced Statistical Modeling – University of Minnesota/Mille Lacs Band of Ojibwe – Minneapolis, MN – September, 2018 to May, 2020

Held weekly sessions with undergraduate students to help understanding of core statistical concepts.

Topics included likelihood estimators, generalized linear models, multi-level models, longitudinal models, and tests for model comparison and fit.

Performed all analysis and statistical programming in R

COLLEGE COURSES TAUGHT:

PUBH 7440 Introduction to Bayesian Analysis (3 credits) – UMN School of Public Health, Spring 2021, under Dr. Haitao Chu, to first year School of Public Health students.

PUBH 7405 Biostatistics: Regression (4 credits) – UMN School of Public Health, Fall 2020, under Dr. Haitao Chi, to second year School of Public Health - Biostatistics students

MTH 144 College Algebra (4 credits) – Lac Courte Oreilles Ojibwe Community College, Spring 2011, undergraduate proctoring other undergraduate students in a televised setting with the University of Wisconsin River Falls Math professor (due to lack of math instuctors at the community college).

Guest Lecturer – HIST 97P: “What is Indigenous History?” (3 credits) – Harvard University, Fall 2001, attested to reservation life as a kid growing up in the Ojibwe culture.

UNIVERSITY LEADERSHIP:

AI Club – University of Minnesota – Minneapolis, MN – September 2019 to May 2022

AI Investment Officer

Developed a new leadership role in the AI Club based on Kaggle competition placement

All investment work done in paper-trading, for research purposes

Collaborated with fellow club members to research and evaluate investment opportunities in the field of Artificial Intelligence.

Analyzed AI-related companies and technologies to identify potential investment targets.

Presented investment recommendations and strategies to the club based on thorough research and market analysis.

Contributed to discussions on AI trends and developments, fostering a deeper understanding of AI's impact on the financial markets.

Blockchain Club – University of Minnesota – Minneapolis, MN – September 2019 to May 2021

AI Investment Officer

Developed a key role in the club's exploration of investment opportunities within the Blockchain and cryptocurrency space.

Conducted research on Blockchain projects, cryptocurrencies, and related technologies to assess their investment potential.

Presented investment proposals and strategies to club members, facilitating informed decision-making.

Participated in discussions on emerging Blockchain trends and their implications for the financial sector.

SKILLS:

Study designs, sample size calculations, and statistical modeling

Python, SQL, R, and SAS programming – 5 years

Quantitative trading, Stock and crypto markets

Financial Market knowledge

Risk Management

Data Visualization

Predictive Analytics and Modeling

SAP creation

Data visualization

Data mining

Statistical inference and modeling

Missing data imputation

Longitudinal data analysis

Survival analysis

Interpretation skills

All stages clinical trial design

SAS (BASE, STAT, MACRO,…)

R Packages to explore statistical models for clinical study design

nQuery and PASS to do power and sample size calculations

Advanced MS Excel

Machine Learning - time series, regression, classification models

Artificial Intelligence Application creation

Synthetic data generation to solve low sample sizes

RESEARCH:

St. Germaine, R (2023). “Generative Adversarial Networks to resolve common data problems experienced by tribal populations: A novel methodology to tribal population research.” University of Minnesota – School of Public Health. Successful Oral Dissertation Defense in the Mayo building School of Medicine - Minneapolis, MN.

St. Germaine, R (2022). “Decision making in quantitative research: LSTM and CNN combinations.” St. Germaine Data Innovations. Invited breakout session at Institute of Mathematical Statistics London Meeting 2022 in London, United Kingdom.

St. Germaine, R (2022). “Quantitative trading decision making: Natural language processing combinations for signaling purposes.” St. Germaine Data Innovations. Invited breakout session at Institute of Mathematical Statistics International Conference on Statistics and Data Science in Florence, Italy.

St. Germaine, R. and St. Germaine, M (2022). “Neural network derived synthetic populations to mitigate small sample sizes.” St. Germaine Data Innovations. Session Presentation at the 2022 National Indian Health Board Annual Meeting.

St. Germaine, R. (2022). “Neural network derived synthetic populations to mitigate small sample sizes.” St. Germaine Data Innovations. Session Presentation at the 2022 Open Data Science Conference West in Las Angeles, California.

St. Germaine, R. (2021). “Methods in clinical data cleaning: A statistical methods approach.” Medtronic. Lecturer at the 2021 American Indian Science and Engineering Society National Conference in Phoenix, Arizona.

St. Germaine, R. (2021). “Automation of clinical data cleaning: A Python tool.” University of Minnesota-Twin Cities School of Public Health. Master Thesis Presentation and Defense at Mayo Building School of Medicine.

St. Germaine, R. and Haitao, C. (2021). “Statistical analyses to detect and refine genetic associations with American Indian cardiovascular diseases.” University of Minnesota-Twin Cities School of Public Health. Oral Presentation at Student of the Month-School of Public Health in the Mayo Building School of Medicine.

St. Germaine, R. and Frizzel, L (2020). “Response bias in clinical trials in American Indian healthcare” University of Minnesota-Twin Cities School of Public Health. Oral Presentation at the Mayo Building School of Medicine.

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