Data Scientist

  • Nautilus Labs
  • New York, NY, USA
  • Jul 18, 2020

Job Description

About Nautilus.

Nautilus is building artificial intelligence to advance the efficiency of ocean commerce. We deliver technology to help shipping companies minimize fuel consumption, maximize operational efficiency, and optimize fleet performance. By arming ship owners and operators with real-time predictive decision support, Nautilus is reducing greenhouse gas emissions and making global trade sustainable.

Ocean shipping consumes over $100 billion dollars of fuel every year, and up to 30% of it can be saved. For owner-operators, reliance on manually collected and analyzed data makes it difficult to optimize fleet performance in real-time. By providing a unified data platform that leverages machine learning, Nautilus helps its clients make better decisions to maximize the return on each ship and every voyage. For our clients, this means they drive closer collaboration, greater transparency, and stronger accountability across their global teams every day.

About you.

Nautilus Labs is looking for a data scientist to join our team. You are inquisitive and enjoy exploring new research questions, and are capable of working largely independently. You have a background in data science, physics, naval architecture, mechanical engineering, or other related quantitative field. You have experience conducting technical investigations with real-world data, and are able to collaborate with and communicate findings clearly with colleagues across the organization. Experience with outlier detection, regression modeling, and optimization methods is preferred. Interest in and knowledge of Bayesian methods for data analysis and modeling is a plus, as is familiarity with maritime, oceanographic, and meteorological data.

Outcomes for this role.

In this role, you will be responsible for conducting analysis of maritime ship and weather data to detect trends and develop predictive models. You will work closely with other data scientists, data analysts, and software engineers to build, test, and deploy robust ship performance models. You will partner with our product team to help conceptualize, design, and implement new machine learning-based products. While we are a collaborative team, you will also be expected to take independent ownership of specific research projects.  Your research and data analysis will help drive decision-making and product development throughout the Nautilus team.  

Proficiencies.
  • 3-5 years of professional experience with a background in data science, physics, naval architecture, mechanical engineering, or other related quantitative field.
  • Strong analytical skills and knowledge of the technical and statistical underpinning of typical data science methods.
  • Working knowledge of the Python data science stack is required; SQL, R or other data analysis languages are also valuable.
  • Experience conducting technical investigations with real-world data.
  • Collaborative with strong communication skills.   
  • Experience with outlier detection, regression modeling, and optimization methods is preferred.
  • Interest in and knowledge of Bayesian methods for data analysis and modeling is a plus, as is familiarity with maritime, oceanographic, and meteorological data.

Our core values.

Get ready to join a group of diverse, smart, talented, and driven individuals. We are looking for people who are motivated by environmentalism and a future where shipping is sustainable and safe. A team member joining Nautilus is...

  • We’re THOUGHTFUL, with a bias towards action.
  • We’re an INCLUSIVE crew, and we are not passengers along for the ride.
  • We’re DIRECT and we ask the tough questions.
  • We EMPATHIZE with humanity.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Organization Type

Company  

Organization Size

11-50  

Sectors

Energy, Transportation