Forward Deployed Data Scientist

About Signal Ocean:

Signal Ocean is the technology arm of the Signal Group. Our primary product, The Signal Ocean Platform, helps shipping and commodities professionals navigate their complex decision making. Driven by advanced machine learning and artificial intelligence, our technology suite provides tailored, exclusive insights that support our clients in achieving performance and efficiency. By securely handling and combining private and public shipping data flows, and applying advanced analytics, insights are delivered over web and mobile applications, as well as through a rich set of APIs and SDKs. Our backend architecture is abstracted to modularly offer deep analytics capabilities that are leveraged in the solutions that we offer or can be directly embedded in our client’s system topologies.

Summary 

Signal is looking for a Forward Deployed Data Scientist to join our high-growth team. This is not your typical data role—you’ll sit at the crossroads of data, engineering, technical pre-sales, and product design, working side-by-side with commercial teams and enterprise clients to design, prototype, and deliver scalable data solutions that drive adoption and revenue.

What You’ll Do:

Client-Centric Data Solutions

• Collaborate with clients, sales, and account teams to uncover real-world data needs and friction points.
• Build working data products—from custom Python pipelines and enriched datasets to Power BI templates and Snowflake-ready views.
• Support pre- and post-sales with prototypes, demos, onboarding materials, and technical discovery.
• Act as a trusted technical advisor, helping clients see the value in Signal’s unique data assets.

Forward Engineering & Product Innovation

• Prototype new data delivery interfaces (APIs, data warehouses, SDKs, BI integrations).
• Co-create new metrics and models (e.g., congestion scores, freight indices) with data scientists.
• Test experimental APIs with design partners and shape future productization plans.

API Optimization & Documentation

• Shape how Signal’s data is accessed and delivered (batch vs real-time, API vs warehouse).
• Own external-facing documentation—making it clear, modern, and actionable for all audiences.
• Improve SDKs and onboarding materials; remove outdated examples and create client-relevant ones.

Usage Intelligence & Feedback Loops

• Track client usage across APIs and data products; uncover what’s working and what needs improvement.
• Reframe underused assets for higher impact and increased adoption.

Feed real client metrics back into engineering and product roadmaps.

Requirements

What You Bring:

• 5+ years in data-heavy roles (e.g., Data Engineer, Data Analyst, Sata Scientist, API developer, etc.)
• You have extensive experience working in client facing roles
• Strong command of Python, SQL, and API schemas—and the ability to explain them clearly.
• Deep experience building or deploying data products in commercial settings.
• Strong business acumen; you get how data is used, not just how it’s built.
• Passion for working directly with clients and solving complex, high-value problems.
• Comfortable operating across both technical and commercial teams.
• Experience in cloud infrastructure, software engineering, or analytics frameworks a plus.
• A curious mind—especially if you’re excited to learn about industries like shipping and commodities trading.

Benefits

What We Offer:

• Generous compensation with additional performance incentives.
• Coverage under the company’s collective health insurance plan.
• Opportunity to work alongside experienced people with deep knowledge in software engineering, data science & shipping business who are always eager to mentor.
• Signal’s hybrid remote work policy currently includes 6 working days at premises per month
• 2-4 weeks of onboarding training to prepare you for your new role, having the opportunity to meet about 30 trainers while diving deep into our products and/or the shipping world.
• Career growth opportunities and a structured development discussion every 4 months.
• Personal learning budget for training, seminars, conferences (750 to 2000 EUR annually depending on seniority).
• Regular team bonding events and activities.