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Global Fishing Watch almost 2 years ago
location: remotework from anywhere
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Junior Data Scientist

Location: Remote – we welcome candidates based in any country

Working Hours: Global Fishing Watch supports flexible working, so the pattern of hours may vary according to operational and personal needs. Global Fishing Watch works across different time zones and weekend work may be required on occasion. The post holder may be required to undertake periodic domestic and international travel. No overtime is payable.

Compensation: Commensurate with experience. Global Fishing Watch offers pension/retirement, health and other benefits commensurate with similar level Global Fishing Watch employees in the country of employment.

Equal Opportunities: GFW is an equal opportunities employer. We hire and promote qualified professionals without regard to actual or perceived race, color, religion, sex, sexual orientation, gender, national origin, age, disability, or any other characteristic protected by applicable law. We believe that our mission is best advanced when welcoming the contributions of people of erse backgrounds, beliefs and cultures. We are committed to providing an inclusive and welcoming environment for all employees of GFW and our partners, vendors, suppliers and contractors.

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.

The Position: The Research and Innovation team at Global Fishing Watch connects data science and machine learning experts with leaders in the scientific community to produce new datasets, publish impactful research, and empower others to use our data. This work aims to harness the potential of satellite technology, machine learning, and big data to shed light on some of the most pressing issues facing the ocean.

The Junior Data Scientist will play a key role on the Research and Innovation team by coordinating the team’s engagement with the research community. In this capacity, they will organize workshops, webinars, brainstorming sessions, and other engagements that foster collaboration between GFW and leading experts on critical ocean issues. Outside of these responsibilities, they will provide general data science support for our portfolio of research projects. Examples of this work include integrating complex data from multiple sources to expand GFW’s dataset of vessel identity, correlating vessel GPS locations with vessel detections from satellite imagery, and generating and publishing gridded products of vessel activity for fishing and non-fishing vessels.

The incumbent will gain experience working with leading researchers and will interface daily with GFW’s team of data scientists and machine learning experts. They will develop erse technical skills in programming, big data, and cloud computing while working for a globally erse, fully distributed, and growing organization. The successful candidate will be highly organized and excited to help Global Fishing Watch develop strong partnerships and cutting-edge science. They should also have demonstrated experience working with complex datasets, analytical research, and communication.

Principal Duties and Responsibilities

Research network engagement

  • Coordinate engagement with GFW research partners by managing communications, organizing workshops, and tracking projects and impacts.
  • Outreach designed to assist partners and the public with accessing and understanding GFW data, including developing webinars, tutorials, and code libraries.
  • Provide data science capacity, such as developing queries, models, and visualizations that support novel research projects for publication in peer-reviewed journals.

Internal research support

  • Provide technical support for the development, advancement, and publication of GFW datasets.
  • Analyze large amounts of data from various sources, such as vessel activity, identity, and satellite imagery to identify trends, anomalies, and insights.
  • Assist with data labelling to expand and improve training datasets.
  • Quality assurance of key data pipelines and research tables and coordinating their effective use by internal teams and external partners.

Candidate Description

Skills you should have

  • Bachelor’s degree in computer science, ecology, or a related field
  • Highly organized, analytical, detail-oriented and self-motivated
  • Experience engaging with academic researchers
  • Demonstrated experience and data science skills with Python or R
  • Ability to work with large datasets and visualize data effectively
  • Experience with version control software and collaboration tools such as git and GitHub
  • Ability to work efficiently to a very high standard of detail while managing multiple priorities
  • Willingness to take ownership of projects and effectively communicate updates in a transparent and proactive manner

Also great

  • Graduate degree and experience with the peer-review process
  • Familiarity with issues of marine ecology or policy
  • Some experience with database query languages such as SQL
  • Experience in geospatial analysis of remotely sensed data
  • An understanding of the complexities and collaboration required to work effectively for a globally remote organization