Nicole Goebel

About Nicole Goebel

My career objective is to leverage experiences gained throughout my academic and startup tenure, utilizing research, data analyses and software skills to tackle challenging and interesting problems of critical value to humanity (environment, education, health). As a Research Scientist with a Ph.D. in Marine Science, I acquired a strong background in ecology and marine ecosystem modeling, with 20+ publications in peer-reviewed journals. I eventually pivoted from academia to Data Science, where I obtained a certificate in Computing for Data Analysis from Coursera.As a Data Scientist at Aclima, I continued to apply my skills in data analysis, visualization, predictive modeling, and machine learning through analysis of terabytes of data streaming from air quality sensors. Through the development of hypotheses, designing experiments, formulating models, and extracting valuable and interesting insights I helped to inform potential improvements for the health and well-being of people and the planet. During my nearly 9-year tenure at Aclima, I also sharpened my software developer skillsets, putting my own models and code into production. I really enjoyed collaborating with a diverse and talented team of engineers, scientists, and designers, and communicating my findings through presentations and reports. I am looking for opportunities to continue learning, growing, and contributing to a great company that is leveraging data in impactful and environmentally aware ways.Tools and Technologies: Python (Pandas, SciKit-learn, Scipy, Numpy, Seaborn, Jupyter), R, Matlab, SQL/BigQuery (+Google Cloud), Git, Vim, Fortran, Unix command shell, netCDF operators (7+ years) and Distributed Computing (Kubernetes, MPI, MapReduce).Analytics and Algorithms: rigorous statistical methods (descriptive, empirical, nonparametric Monte Carlo/boot-strap, error propagation, probability distributions, auto/de-correlation), supervised and non-supervised machine learning algorithms including clustering (k-Means, H/DBSCAN), classification (logistic regression, K-nearest neighbors, decision trees, SVM), regression (multi/linear, decision trees, random forests), dimensionality reduction (PCA, feature selection), data preprocessing (standardization, transformation, imputation) and model tuning, evaluation and selection techniques (RMSE, ROC).Soft Skills: Critical Thinking, Problem Solving, Adaptability, Communication, Collaboration, Public SpeakingOutdoor Passions: Mountain Biking, Gravel Biking, Kite Surfing, Skiing, Rock Climbing, Scuba Diving, Swimming, Surfing

Experience

1. Data Scientist

   Getproven

   Jan 2024 — Present

   I work as a data scientist at GetProven.com, where I analyze thousands of data points from our SaaS platform to uncover patterns and user behaviors. I use statistical analysis, machine learning, and data visualization to generate insights that drive product improvements and business decisions.

Education

• University of Illinois Urbana-Champaign

  Bachelor of Science, Biology

  1990 — 1994

• University of Otago

  Ph.D., Marine Science, Phytoplankton Ecology of Fiordland, New Zealand

  1997 — 2002

Skills

• R
• Experimental Design
• Ecology
• Scientific Writing
• Bioinformatics
• Data Analysis
• Matlab
• Biology
• Environmental Science
• Science
• Molecular Biology
• Coastal
• Microbiology
• Numerical Analysis
• Genetics
• Marine Biology
• Oceanography
• Statistics
• Microscopy
• Python
• Remote Sensing
• Field Work