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Global Fishing Watch

Data Scientist - Vessel Identity

Remote

November 7


Responsibilities

Vessel identity research

  • Support research summarizing the identity and activity of fishing vessels that operate outside of a flag State’s national waters (Year 1 focus)
  • Coordinate with the external research partners collaborating on vessel identity (including vessel ownership) and help them with data requests, analysis support, and research publications.
  • Improve the classifications of types and characteristics of all industrial vessels through consulting various stakeholders, in collaboration with our Product team, to improve its consistency, cohesion, and usefulness of our datasets and vessel classification model. 
  • Provide data science support to other projects related to vessel identity, as needed.

Data improvement and data sharing 

  • Oversee and improve the regular data collection process of vessel registry in coordination with the engineering team to ensure a high standard of vessel identity database. 
  • Improve and scale up our database of fishing and non-fishing vessels through unstructured data mining, natural language processing, and the engagement of public and private vessel identity data owners. 
  • Provide analysis and general technical support to help develop and publish GFW datasets on vessel identity. 
  • Help enhance vessel identity data with hull identifiers and produce training datasets for improved vessel behavioral/classification models.
  • Help build a comprehensive public vessel identity platform


Requirements

Skills you should have

  • Bachelor's degree and at least five years of professional experience, or an equivalent combination of education and experience, in computer science, ecology, fisheries, or a related field
  • Demonstrated experience and data science skills with Python (preferred) or R 
  • Highly organized, analytical, detail-oriented and self-motivated
  • Ability to work with large datasets and visualize data effectively
  • Ability to work efficiently to a very high standard of detail while managing multiple priorities
  • Experience with version control software and collaboration tools such as Git and GitHub
  • Willingness to take ownership of projects and effectively communicate updates in a transparent and proactive manner

Also great

  • Experience in data mining, web scraping, natural language processing, and automated processes using docker containers and Airflow
  • Some experience with database query languages such as SQL
  • Familiarity with issues of international fisheries policy and management
  • An understanding of the complexities and collaboration required to work effectively for a globally remote organization
  • Graduate degree and experience with the peer-review process and engaging with academic researchers
  •  If you don't think you check all the boxes, but believe you have unique skills that make you a great fit for the role, we want to hear from you!


Company Background

Global Fishing Watch is an international, non-profit organization committed to advancing ocean governance through increased transparency. We create and publicly share knowledge about human activity at sea to enable fair and sustainable use of our ocean. Founded in 2015 through a collaboration between Oceana, SkyTruth, and Google, GFW became an independent non-profit organization in June 2017. Using cutting-edge technology, we create and publicly share map visualizations, data and analysis tools to enable scientific research and drive a transformation in how we manage our ocean. Our major focus is on commercial fishing because it is the most widespread human activity at sea, the most impactful on ocean health, and the most crucial for global livelihoods and food security. By 2030, we aim to monitor and visualize the impact of ocean-going vessels, both industrial and small-scale, that are responsible for the vast majority of the global seafood catch. We believe human activity at sea should be common knowledge in order to safeguard the global ocean commons for the common good of all.