Senior Environmental Data Scientist

Ocean OS | London | apply.workable.com |
Job Title: Senior Environmental Data Scientist (Marine Biologist)
Reports To: CEO
Classification: Full-time
Term: Permanent
Dates: Start ASAP
Location: Remote, London preferred

About Us:

OceanOS is at the forefront of a transformative wave in environmental monitoring, particularly focused on marine and coastal ecosystems. Our mission is to harness cutting-edge technologies to provide unparalleled insights into the health of our planet's most vital and vulnerable habitats.
With a foundation rooted in innovation, sustainability, and a deep commitment to the oceans that sustain life on Earth, we are building solutions that not only monitor but also protect and restore the natural world.

Joining OceanOS means becoming part of a passionate team dedicated to making a significant, positive impact on global marine biodiversity. We invite you to be a cornerstone in our journey, where your work directly contributes to safeguarding and understanding our blue planet for generations to come.

Description:

We are seeking a highly skilled and dedicated Senior Data Scientist, with strong experience in the marine environmental sciences, to join our team. We also welcome applications from a Marine Biologist or Environmental Scientist that can demonstrate strong proficiency and experience in the field of data science.
The candidate will be tasked with processing, analysing, and interpreting data from our cutting-edge marine biodiversity monitoring system. The successful candidate will play a crucial role in transforming raw data into actionable insights to inform environmental impact assessments and support decision-making for sustainable offshore wind development.

Responsibilities:

 •  Process and integrate diverse datasets from eDNA, passive acoustic monitoring, and environmental sensors, ensuring data quality, consistency, and compatibility.
 •  Develop and implement data analysis pipelines using statistical methods, including machine learning techniques, to identify patterns, trends, and relationships in the monitoring data.
 •  Interpret analysis results in the context of marine ecology, offshore wind impacts, and relevant environmental regulations and policies.
 •  Collaborate with cross-functional teams, including ecologists, marine biologists, and survey specialists, to refine monitoring strategies and address stakeholder needs.
 •  Prepare technical reports, data visualisations, and presentations to communicate findings and recommendations to diverse audiences.
 •  Maintain and update data management systems, ensuring data security, access control, and version control.
 •  Stay up-to-date with advancements in marine environmental data science, statistical methods, and relevant technologies, and propose innovative solutions to enhance the monitoring system.

Requirements:

 •  Master's degree or PhD in Environmental Science, Marine Biology, Oceanography, Ecology, Data Science, or a related field.
 •  Strong background in statistical analysis, data visualisation, and programming (e.g., R, Python, SQL).
 •  Experience working with large, complex datasets, preferably in the context of ecology, marine environments or renewable energy.
 •  Knowledge of marine ecology, biodiversity assessment methods, and environmental impact assessment processes.
 •  Familiarity with either eDNA, passive acoustic monitoring, or another emerging marine monitoring technology.
 •  Excellent problem-solving, critical thinking, and communication skills.
 •  Ability to work independently and collaboratively in a fast-paced, multidisciplinary team environment.
 •  Proficiency in data management, quality assurance, and documentation practices.
 •  Passion for applying data science to support sustainable marine resource management and conservation.

Preferred Qualifications:

 •  Experience in applying machine learning and artificial intelligence techniques to ecological data analysis, such as species distribution modelling, biodiversity assessment, and ecosystem health indicators.
 •  Experience with spatial analysis, GIS, and remote sensing techniques.
 •  Familiarity with offshore wind energy development and associated environmental regulations.
 •  Track record of publishing scientific papers or presenting at conferences in relevant fields.
 •  Experience working with stakeholders from industry, government, and academia.

We offer a competitive salary combined with an attractive equity package, giving you the opportunity to grow with the company and share in its success. As an early-stage startup, we provide a dynamic and collaborative work environment. You'll have the chance to work on cutting-edge projects at the intersection of marine conservation, renewable energy, and artificial intelligence, while developing your skills and expertise in a supportive and innovative team.
We value work-life balance and offer flexible working arrangements to support your well-being. If you are passionate about leveraging data science and ML/AI to drive the development of a sustainable blue economy, then we encourage you to apply for this exciting opportunity and join us in shaping the future of marine environmental monitoring.

Requirements
 •  Master's degree or PhD in Environmental Science, Marine Biology, Oceanography, Ecology, Data Science, or a related field.
 •  Strong background in statistical analysis, data visualisation, and programming (e.g., R, Python, SQL).
 •  Experience working with large, complex datasets, preferably in the context of ecology, marine environments or renewable energy.
 •  Knowledge of marine ecology, biodiversity assessment methods, and environmental impact assessment processes.
 •  Familiarity with either eDNA, passive acoustic monitoring, or another emerging marine monitoring technology.
 •  Excellent problem-solving, critical thinking, and communication skills.
 •  Ability to work independently and collaboratively in a fast-paced, multidisciplinary team environment.
 •  Proficiency in data management, quality assurance, and documentation practices.
 •  Passion for applying data science to support sustainable marine resource management and conservation.
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