Data Scientist

Company Intelligence

Cognite is a global leader in Industrial AI, providing an industrial data platform that helps manage sensors and data in manufacturing facilities, with a $2 billion unicorn valuation as one of Norway's top startups. Founded in Norway, the company recently relocated its global headquarters to Tempe, Arizona (opened December 3, 2025), shifting focus to North America's tech ecosystem, especially semiconductors, to drive growth and serve clients generating billions of data points daily. It holds awards like 2022 Technology Innovation Leader for Global Digital Industrial Platforms and 2024 Microsoft Energy and Resources recognition, positioning it strongly in industrial software. Recent developments include product launches like NEAT 1.0 for scalable data modeling in Cognite Data Fusion, emphasizing AI-ready knowledge graphs and governance. The company culture prioritizes innovation in industrial transformation, with a strategic North American expansion for partnerships and job creation. Core values center on AI-driven operational value, as seen in hundreds of millions unlocked for customers. Primary office is now the Arizona HQ; the listed role is remote in the US, aligning with flexible policies amid global operations.

Program Deep Dive

This is a mid-level Data Scientist role (not explicitly an internship/graduate program), remote in the US, suited for recent graduates (18-25) with strong data skills transitioning to industrial AI[web:1 from query context]. Structure involves full-time contributions to data platforms like Cognite Data Fusion, with ongoing product updates indicating iterative learning via tools like NEAT for data modeling. Key skills sought: expertise in data modeling, AI scalability, physical asset modeling, validators for quality checks, and handling industrial datasets (sensors, graphs); proficiency in Python/object-oriented tools implied for NEAT integration. Daily responsibilities include building/deploying data models, pre-deployment analysis (dry-runs, severity scoring), issue resolution via interactive tools, and supporting industrial clients in manufacturing/semiconductors. Learning opportunities stem from Cognite's Academy (8,600+ resources) and product tooling for real-world AI in operations. Mentorship likely through engineering teams (e.g., managers overseeing industrial experiences), with career paths to senior roles in Industrial AI platforms, given rapid growth and unicorn status.

Application Success Guide

Apply via the provided URL (https://www.remoterocketship.com/jobs/mid-level-data-scientist/); no specific deadlines listed, but apply promptly as remote US roles fill quickly—check Lever jobs for Cognite openings. Step-by-step process:

1. Tailor resume to highlight data modeling/AI projects (e.g., GitHub with scalable models);
2. Submit via Remote Rocketship/Lever with cover letter linking skills to industrial data (sensors, graphs);
3. Complete any technical assessments on data platforms;
4. Virtual interviews focusing on case studies. Common interview questions: "How would you build a scalable data model for industrial sensors?" "Explain dry-run analysis for deployment risks." "Describe validating a knowledge graph in Cognite Data Fusion." Expect case studies on NEAT-like tools: model a physical asset graph, fix issues with validators, simulate pre-deployment changes. Standout candidates demonstrate industrial applications (e.g., manufacturing data pipelines) over generic ML, plus US remote adaptability.

Insider Tips

Cognite values technical depth in industrial AI (e.g., data fusion for billions of points) over pure soft skills—prioritize Python for graph modeling, NEAT validators, and scalability. Show industry knowledge in semiconductors/manufacturing (Arizona hub), citing sensor data challenges and Cognite's value unlocks. Interview tips: Reference recent HQ move and NEAT 1.0 to signal research; practice object-oriented data tooling demos. Questions to ask: "How does the Arizona HQ integrate with remote Data Scientists on global client projects?" "What upcoming features in Cognite Data Fusion will impact data modeling workflows?" Avoid red flags: Generic resumes without industrial examples; ignoring remote US timezone alignment; lacking specifics on graph governance or legacy tool migrations.

Practical Information

Salary for mid-level Data Scientist (remote US): Typically $120K-$160K base (industry benchmark for industrial AI unicorns; confirm via application), with equity potential given $2B valuation. Benefits likely include standard tech perks (health, 401k, unlimited PTO) plus Cognite Academy access for training. Program duration: Full-time indefinite, not fixed internship; start dates flexible post-hire, targeting Q1 2026 amid growth. Networking: Leverage Arizona ecosystem events, Microsoft partnerships, and alumni via Cognite Hub/product communities for industrial AI connections.