Data Scientist Industrial Datacognite

Company Intelligence

Cognite is a global leader in Industrial AI and Data, providing a scalable platform (Cognite Data Fusion) that operationalizes industrial data for energy, manufacturing, power & renewables sectors to enhance safety, sustainability, and profitability. The company focuses on AI-driven workflows, knowledge graphs, and real-time data collaboration, targeting $100B in customer value by 2035 through partnerships like NVIDIA for advanced forecasting. Recent developments include being named a Leader in the IDC MarketScape for Worldwide Industrial DataOps Platforms (March
2026. and a Q1 2026 product release accelerating workflows with AI agents, data transformation UIs, and 465% ROI for customers. Strategic directions emphasize ecosystem integrations, automation, and predictive analytics for asset-heavy operations. Cognite supports remote work, as seen in US-based roles, with a user-friendly platform for field-to-remote decision-making. Core offices are not detailed in recent sources, but global operations span energy and manufacturing hubs; culture prioritizes trust, security, scalability, and industrial-specific AI innovation.

Program Deep Dive

This is a mid-level Data Scientist role focused on Industrial Data at Cognite, remote in the US, suited for recent graduates (18-25) with strong analytical skills transitioning to industrial AI. Structure involves applying math, statistics, ML, optimization, or agentic workflows to industrial problems like data pipelines, knowledge graphs, and AI agents for workflows (e.g., root cause analysis, sensor data syncing). Daily responsibilities include translating industrial challenges into analytics, building/maintaining data models, extractors for ingestion, and AI integrations (e.g., NVIDIA NV-Tesseract for forecasting). Learning opportunities cover Cognite Data Fusion features like data modeling, knowledge graphs, extraction pipelines, and troubleshooting SDKs. Mentorship likely involves team collaboration on platform velocity and customer value delivery; career paths progress to senior data science or management roles in Industrial AI, leveraging ecosystem partnerships.

Application Success Guide

Apply via the provided URL (https://www.remoterocketship.com/jobs/mid-level-data-scientist/); no specific deadlines listed—submit promptly as remote US roles fill quickly.[Original Query] Requirements: Strong applied background in mathematics, statistics, ML, optimization, agentic workflows; ability to handle industrial data problems analytically. Step-by-step:

1. Tailor resume to highlight ML projects on time-series/industrial data;
2. Submit via Remote Rocketship portal;
3. Prepare for technical screens on Python SDK, data pipelines. Common interviews: "Translate an industrial problem (e.g., downtime prediction) into an ML model"; "Explain knowledge graph for sensor data"; behavioral on problem-solving in asset-heavy ops. Expect case studies on data ingestion/extractors or AI workflow optimization; no assessment centers noted. Standout candidates demonstrate industrial context (e.g., energy/manufacturing datasets) via GitHub projects or coursework.

Insider Tips

Cognite values technical depth in industrial DataOps (e.g., knowledge graphs, AI agents) over pure soft skills—prioritize ML/optimization portfolios showing real-world scalability. Demonstrate industry knowledge: Reference Industrial AI trends like predictive maintenance, NVIDIA integrations, or DataOps platforms. Interview tips: Use STAR method for industrial examples; code live on data transformation or extractor configs. Questions to ask: "How does the team measure AI agent impact on customer ROI?" or "What's next for NVIDIA Tesseract in workflows?" to show alignment with $100B goal. Avoid red flags: Generic resumes without industrial examples; ignoring security/scalability in tech answers; no questions on platform ecosystem.

Practical Information

Salary for mid-level Data Scientist (remote US): Not specified; industry benchmarks for similar Industrial AI roles range $120K-$160K base, plus equity/bonuses—research Glassdoor for Cognite specifics. Benefits: Secure platform access, likely standard tech perks (health, remote stipend); focus on professional growth via courses on CDF features. Start dates: Rolling, align with Q1 releases (e.g., post-March 2026). Duration: Full-time permanent, not fixed internship—ideal for grads seeking progression.[Original Query] Networking: Engage Cognite Hub for product updates/courses; LinkedIn for alumni in Industrial AI; follow releases for partnership events (e.g., Koch Ag, Celanese). Join extractor/ML communities for connections.