Vessel Data Manager

Nautilus Labs
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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.

Implementation and Client Success owns the client relationship post-sales. The group’s goal is to maximize client value with every interaction including pre-sales support, ship activation, onboarding/training users, uncovering valuable data insights, monitoring client health, identifying upsell opportunities and obtaining public-facing client testimonials. The team consists of Integrations Specialists who handle ship integrations, Client Success Managers who work with a set of named accounts, and Managed Services who support client daily operations to help customers optimize their fleets. Together these teams are responsible for empowering our clients to become expert users and achieving amazing results.

We are looking for a Vessel Data Manager who is an organized problem solver and has a proven track record for effectively documenting and communicating complex data issues.

They will know how to manage integrations of vessel data from our client’s ships and also how to reliably persist that data in our platform, in order to allow its analysis using machine learning. They will be working in a challenging and dynamic environment where they will solve issues that occur in vessel data from maritime clients and influence how high quality insights are provided through Nautilus Platform.

Outcomes for the Role.

  • Review data issues raised in client data or seen in Nautilus platform and independently determine root cause of the issues
  • Debugging data transmission issues and investigating strange or abnormal data patterns
  • Supporting existing hardware and software integrations and debugging problems that might occur
  • Organize and manage how data issues are tracked and addressed across 100-200 live vessels
  • Effectively leverage JIRA tickets and other internal tools to loop in the necessary internal stakeholders for problem-solving
  • Collaborate with Implementation team members in end-to-end testing of vessels in platform before go-live
  • Support Client Success Managers with existing clients by being the internal point person regarding data setup and troubleshooting for live vessels
  • Work independently as well as collaborate across multiple teams across multiple hubs
  • Clearly communicate with clients to gather information during data issue investigations
  • Assisting the engineering team by validating and understanding vessel data
  • Assisting the sales team as a technical resource

Proficiencies.

  • 3+ years of overall professional experience
  • 1+ years of work experience in a shipping company preferred
  • Ability to work across different time zones (Singapore specifically)
  • Understanding of ship machinery and systems
  • Write effective emails in business English that translate well to international stakeholders
  • Clearly and concisely communicate technical questions and answers related to data by combining visuals and text
  • Flexible critical thinking and analytical skills with an ability to find drivers behind the data
  • Inquisitive to dive deep into data to investigate anomalies
  • Advanced proficiency in Excel
  • Experience with relational databases, and Python or JS programming language preferred
  • Self motivated and resourceful, ready to learn new skills along the way
  • Working knowledge and/or specialized understanding of APIs, HTML, XML, Web Services, REST services and other widely used Internet-based technologies would be a plus
  • BA/BS degree in a quantitative field (e.g. Engineering, Science etc) preferred
  • Ability to collaborate and communicate effectively with team members across time zones

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.

Location: Bengaluru (Bangalore), India

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.

Company Info.

Nautilus Labs

Nautilus Labs is the leading technology partner for the profitable decarbonization of the ocean supply chain. Our solutions are helping owners, operators and charterers improve efficiency, reduce fuel consumption and develop better commercial relationships. With hubs in New York, Singapore, London, Paris, Athens, and Bangalore, we are backed by top venture capital firms and investors, such as the Microsoft Climate Innovation Fund and M12.

  • Industry
    Artificial intelligence,Computer software
  • No. of Employees
    84
  • Location
    New York, NY, USA
  • Website
  • Jobs Posted

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Nautilus Labs is currently hiring Data Manager Jobs in Bengaluru, Karnataka, India with average base salary of ₹90,000 - ₹250,000 / Year.

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