Niko Hartline

Niko Hartline

Environmental Scientist

Research Analyst

Data Analyst

About Me

Using data to advance new strategies and solve problems

Problem solver

Complicated problems and puzzles are what truly capture my interest. I love finding solutions and have found that my talent for pattern recognition makes me excel at it. Between a fascination with complex problems and a passion for the outdoors, I ended up pursuing the environmental sciences, a field riddled with convoluted issues to be solved. My aim is to apply my multidisciplinary background in economics  Notable Coursework:
► Applied Econometrics
► Natural Resource Economics
► Environmental Economics (3), statistics  Notable Coursework:
► Data Analysis
► Advanced Data Analysis
► Environmental Modeling, policy  Notable Coursework:
► Economics & Environmental Policy
► Environmental Policy & Politics
► Environmental Law & Policy, communication  Notable Coursework:
► Writing for the Environmental Sciences
► Project Management
► Informatics (data visualization), and natural sciences  Notable Coursework:
► Earths Systems Science
► Ecological Principles
► Environmental Biogeochemistry to develop solutions to environmental problems with an economically sound approach.

Data nerd

In my experience with tackling environmental issues such as agriculturally-driven habitat destruction, micropollutants from synthetic apparel, and fisheries policy in Peru, I’ve found that data drives the practical aspects of developing effective solutions. Careful monitoring and analysis form the crucial basis to understanding the outcomes of implemented solutions to provide insight into deficiencies that need to be addressed. It was this realization that led me to prioritize developing skills in statistics, econometrics, R, JMP, MATLAB, and Python to improve my effectiveness as an environmental scientist. In working with these tools, I have also found that I enjoy the problem solving required to write code and perform statistical analyses.

Adventurer

From the Swiss Alps
 to the wilderness of Alaska
 to the wetlands of Brazil
, whenever I visit a new place, the first thought on my mind is how to best experience its natural beauty. I love the feeling of pure awe that nature has to offer whether it be from orcas swimming by our research vessel
, the aurora borealis
 dancing overhead, or a jaguar
 pouncing on an unsuspecting capybara. Moments like these are unforgettable, and I hope to continue finding fortunate opportunities that allow the adventures involved.

Background

Programming

Programming

Past projects have required developing scripts in R, Python, and MATLAB to manipulate datasets and produce professional analyses, graphics, and models.

Data Analysis

Data Analysis

Lead data analyst for a research team collaborating with Patagonia, Inc. and for a small research group in the Tilman Laboratory at UCSB.

Research

Research

Co-author on 5 peer-reviewed publications; 5 major literature reviews (20+ sources each).

Economics

Economics

B.A. in economics. Environmental science degree included substantial training in theoretical and applied environmental economics.

Past Affiliations

https://www.nikohartline.com/wp-content/uploads/2017/09/Bren-Logo-80x80.jpg
https://www.nikohartline.com/wp-content/uploads/2017/09/Patagonia-Logo-80x80.jpg
https://www.nikohartline.com/wp-content/uploads/2017/09/CCBA-Logo-80x80.jpg
https://www.nikohartline.com/wp-content/uploads/2017/09/UH-Manoa-Logo-80x80.png
https://www.nikohartline.com/wp-content/uploads/2017/09/UCSB-Logo-80x80.png
https://www.nikohartline.com/wp-content/uploads/2017/09/MDIBL-Logo-80x80.png

Resume

Recent Courses

Oct 2017 - Dec 2017

CrowdFlower's AI Education Series

Active Learning, Artificial Intelligence, Machine Learning

Hands-on intensive courses using scikit-learn, keras, and tensorflow to implement production-level machine learning techniques including vision and natural language processing. Covered the coding and usage of convolutional neural networks (CNNs), long short-term memory (LSTMs), recurrent neural networks (RNNs), and other machine learning methods in Python. In addition active learning techniques were practiced using crowdsourced survey responses to refine image training sets to improve algorithm performance.

Oct 2017 - present

Machine Learning

Stanford University Online

Andrew Ng's class on theory, application, and coding of machine learning methods using Octave. Reproduced some of the assignments using Python.

Education

2016

Master of Environmental Science and Management

Bren School of Environmental Science & Management - University of California, Santa Barbara

Notable Coursework: Advanced Data Analysis, Applied Econometrics, Environmental Informatics, Energy, Technology, & Environment, Environmental Modeling, Cost-Benefit Analysis, Environmental Law & Policy, and Life Cycle Assessment

2013

Bachelor of Arts in Economics and Environmental Studies

University of California, Santa Barbara

Notable Coursework: Vector Calculus, Energy and the Environment, Renewable Energy, Natural Resource Economics, Writing for the Environmental Sciences, and Environmental Economics

Experience

Nov 2017 - Present

Data Analysis Consultant

EVmatch

Developing a set of scripts to generate reports with graphics, summary statistics, and growth analytics for user data directly from the apps database using PostgreSQL and R (Rmarkdown and ggplot2).

Mar 2015 - Oct 2016

Data Analyst

Patagonia Microfiber Pollution Analysis Project

Quantified synthetic microfiber pollution emitted from machine washing of outdoor clothing for client Patagonia, Inc. Created professional data graphics (30+) to communicate results via report, poster, and oral presentations. Published research in the Environmental Science & Technology journal.

Mar 2016 - June 2016

Web Application Developer

Sustainable Fisheries Group, UCSB

Designed an easily navigated web application dashboard of Peruvian fisheries economic data with user input options for potential policy instruments to provide a reactive graphical interface informing policymakers on effective management strategies.

July 2015 - May 2016

Data Research Assistant

Tilman Laboratory, UCSB

Developed a data mining and analysis program for the International Union for Conservation of Nature (IUCN) Red List of Threatened Species, saving 300+ hours of manual data entry and expanding project scope. Created data graphics of endangered species for publication in journals, book chapters, and presentation to the Ecological Society of America; used Python, Excel, MATLAB, JMP, and R for data mining, analyses, and graphics.

Download Resume

Primary Skills

R

Python

JMP

MATLAB

Octave

Secondary Skills

Microsoft Excel

shiny

GitHub

scikit-learn

keras/tensorflow

PostgreSQL

STATA

HTML/CSS

ArcGIS

Portfolio

Projects
Natural Language Processing and the Red List of Endangered Species
Natural Language Processing and the Red List of Endangered Species
Python
Synthetic Microfiber Pollution from Machine Washing
Synthetic Microfiber Pollution from Machine Washing
R
Anchoveta Web Application (Peru’s Fisheries)
Anchoveta Web Application (Peru’s Fisheries)
Shiny
Data Mining of Global Endangered Species Data
Data Mining of Global Endangered Species Data
Data Mining
Global Endangered Species Modeling and Mapping
Global Endangered Species Modeling and Mapping
JMP
Habitat Destruction and Biodiversity Modeling
Habitat Destruction and Biodiversity Modeling
R
International Union for Conservation of Nature (IUCN) Red List Graphics
International Union for Conservation of Nature (IUCN) Red List Graphics
R
Writing Samples
Writing Samples
Writing

Contact

Get in Touch

Get in Touch

Feel free to send me an email or message in the contact form if you would like more information about me or my projects. Contact about job opportunities or freelance work is also welcome.
Oakland, CA
nikohartline@gmail.com

Extra

Links

My GitHub page: https://github.com/nikohartline
My LinkedIn page: https://www.linkedin.com/in/niko-hartline/
My master's thesis research project team: brenmicroplastics.weebly.com/the-team.html
In the News:

 

Publications

Hartline, N. L., Bruce, N. J., Karba, S. N., Ruff, E. O., Sonar, S. U., & Holden, P. A. (2016). Microfiber masses recovered from conventional machine washing of new or aged garments. Environmental science & technology, 50(21), 11532-11538.

Christie, A. E., Chapline, M. C., Jackson, J. M., Dowda, J. K., Hartline, N., Malecha, S. R., & Lenz, P. H. (2011). Identification, tissue distribution and orexigenic activity of neuropeptide F (NPF) in penaeid shrimp. Journal of Experimental Biology, 214(8), 1386-1396.

Christie, A. E., Nolan, D. H., Garcia, Z. A., McCoole, M. D., Harmon, S. M., Congdon-Jones, B., Ohno, P., Hartline, N., Congdon, C., Baer, K., & Lenz, P. H. (2011). Bioinformatic prediction of arthropod/nematode-like peptides in non-arthropod, non-nematode members of the Ecdysozoa. General and comparative endocrinology, 170(3), 480-486.

Christie, A. E., Nolan, D. H., Ohno, P., Hartline, N., & Lenz, P. H. (2011). Identification of chelicerate neuropeptides using bioinformatics of publicly accessible expressed sequence tags. General and comparative endocrinology, 170(1), 144-155.

Christie, A. E., Durkin, C. S., Hartline, N., Ohno, P., & Lenz, P. H. (2010). Bioinformatic analyses of the publicly accessible crustacean expressed sequence tags (ESTs) reveal numerous novel neuropeptide-encoding precursor proteins, including ones from members of several little studied taxa. General and comparative endocrinology, 167(1), 164-178.

 

Other

Volunteering aboard the research vessel Tiglax assessing zooplankton populations of the Gulf of Alaska: