Welcome to my GitHub profile! I'm a long-time research scientist transitioning to Data Analytics, with extensive experience in managing large datasets, advanced statistical analysis, and software development. Skilled in Python, SQL, and data visualization tools with a proven track record of data-informed decision-making. Seeking to leverage analytical expertise and technical skills to contribute to problem-solving in a dynamic business environment.

📍 Location: Snohomish, WA 98296
📞 Contact: (206)-552-4365 | 📧 [email protected]
🔗 LinkedIn

🏅 Portfolio

Research Analyst
(March 2023 - January 2024)

• Implemented advanced machine learning algorithms on single-cell RNA-seq datasets to identify biomarkers for early detection of disease progression.
• Automated routine data processing tasks using Python and R, reducing processing time by 80% and boosting data reliability.
• Designed interactive dashboards with Tableau and Looker Studio to visualize experimental data trends and findings, significantly improving stakeholder report accessibility.
• Utilized workflow management software to automate large dataset processing on Linux-based cloud computing systems

Research Associate III
(December 2021 - November 2022)

• Engineered and deployed a cloud-based SQL database for real-time high-throughput quality control metrics, allowing for daily reorganization.
• Presented key experimental findings at weekly team meetings and quarterly departmental reviews using interactive Tableau and Looker Studio dashboards.
• Automated experimental data flow and analysis pipelines, increasing data throughput and reducing data handling errors in complex datasets.
• Conducted robust sensitivity/specificity statistical analysis to optimize the parameters of molecular assays, which increased the consistency and reproducibility of experimental results.

Graduate Student / Lab Manager / Lab Technician
(September 2016 - August 2021)

• Developed a novel classification pipeline to segment and analyze cell populations across multi-species datasets.
• Employed statistical tools like NumPy and Pandas to analyze large biological data sets.
• Utilized data viz tools like Seaborn and Plotly to convey significant findings in weekly meetings.
• Enhanced data collection protocols by integrating automated cell counting software, improving data accuracy and reducing manual data entry errors.
• Designed and implemented a cloud-based lab inventory system that streamlined the tracking, ordering, and management of lab supplies, reducing overhead costs by 15% and improving inventory accuracy.

• Programming Languages: Python, SQL, R
• Technologies: Git, Unix, Statistical Analysis (numpy, scikit, scipy)
• Data Visualization: Tableau, Looker Studio, Plotly, ggplot2

• Master of Science (M.S) in Molecular Biology, Washington State University, Pullman, WA
• Bachelor of Science (B.S) in Biochemistry, magna cum laude, Washington State University, Pullman, WA

• Ciccarelli, M., et al. (2020). Donor-derived spermatogenesis following stem cell transplantation in sterile NANOS2 knockout males. Proceedings of the National Academy of Sciences, 117(39).
• Du, G., et al. (2021). Proper timing of a quiescence period in precursor Prospermatogonia is required for stem cell pool establishment in the male germline. Development, 148(9).

• Washington State University Center for Reproductive Biology Retreat, September 2019, Leavenworth, WA. Developmental origins of spermatogonial stem cells.
• Gordon Conference on Germinal Stem Cell Biology, May 2019, Sha Tin, Hong Kong. Relationship between Dppa5a expression and spermatogonial stem cell fate determination in fetal prospermatogonia.

In my quest to further expand my expertise and stay updated with the latest advancements in the field of data analytics, I am currently dedicating time to learn and master the following areas:

• Data Visualization Mastery: Enhancing skills in creating insightful and engaging data visualizations to effectively communicate complex findings and drive data-informed decision-making.
• Natural Language Processing Exploration: Exploring natural language processing (NLP) techniques to extract insights from unstructured text data, with a focus on applications in healthcare and scientific literature analysis.
• Advanced Data Mining Techniques: Learning advanced data mining techniques to discover hidden patterns and relationships in large datasets, with the goal of improving data-driven decision-making processes.
• Geospatial Analysis Proficiency: Developing expertise in geospatial analysis to analyze and visualize data with spatial components, enabling better understanding and decision-making in various fields, including epidemiology and environmental science.

I am always open to discussing these topics further or collaborating on projects related to my areas of learning and expertise. Feel free to reach out!

Feel free to reach out if you're interested in collaborating on projects or if you have questions about my work!