Data Scientist – Predictive Maintenance

🔥 22 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 15%

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TRACTIAN

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2019

🏭 Manufacturing

🔧 Hardware

🤖 Artificial Intelligence

🔥 Funding within the last year

💰 DEBT on 2026-07

Manufacturing • Hardware • Artificial Intelligence

TRACTIAN is a provider of AI-powered hardware and software for multimodal asset health and predictive maintenance. The company combines plug-and-play vibration and electrical sensors with cloud analytics and AI-driven failure diagnostics to deliver real-time monitoring, downtime prevention, unified asset health views, and CMMS/work-order integrations for asset-heavy operations. Tractian targets manufacturing, data centers, oil & gas, mining, government, and other industrial facilities and is used to scale reliability programs and reduce operational risk; the company recently reached a reported $1. 4B valuation after a $130M Series D.

📋 Description

• Develop time-series ML models for anomaly detection, forecasting, behavioral modeling, and condition monitoring using large-scale industrial sensor data. • Translate experimental models into reliable, maintainable, and scalable production systems. • Design metrics, diagnostics, and monitoring mechanisms for data quality, feature distributions, anomaly scores, prediction stability, model drift, and performance. • Investigate modeling strategies balancing predictive performance, generalization, adaptability, interpretability, and maintenance costs. • Develop feature extraction, signal processing, and representation learning techniques for industrial sensor data. • Formulate hypotheses, design controlled experiments, benchmark approaches, and evaluate models using temporal validation and realistic deployment scenarios. • Improve data processing, feature computation, model serving, and inference workflows for high-throughput, low-latency applications. • Evaluate state-of-the-art methods and translate promising techniques into production-ready solutions. • Collaborate with software engineers, product teams, and laboratory specialists to validate models, investigate failures, and improve predictive maintenance products.

🎯 Requirements

• Strong background in machine learning, with practical experience developing models for time-series data, anomaly detection, forecasting, or related sequential modeling problems. • Proficiency in Python and common ML and data processing libraries, such as NumPy, pandas, scikit-learn, PyTorch, or equivalent frameworks. • Experience taking machine learning models from experimentation to production, including code organization, testing, performance optimization, and integration with data or inference pipelines. • Solid understanding of time-series fundamentals, including temporal dependencies, non-stationarity, seasonality, noise, and appropriate validation strategies. • Understanding of data drift and model degradation in production, including techniques for monitoring distribution shifts, evaluating model stability, and identifying when model updates are necessary. • Strong software engineering skills, including writing modular, testable, maintainable code and designing solutions that can operate reliably at scale. • Experience designing experiments and benchmarking models using appropriate metrics, baselines, and validation methodologies. • Ability to analyze complex, noisy, high-dimensional data and translate empirical findings into sound technical decisions. • Proficient in English and Portuguese.

🏖️ Benefits

• Competitive Compensation • 30 days of paid annual leave • Education and courses stipend • Earn a trip anywhere in the world every 4 years • R$1.035/month for meals allowance • Health plan with national coverage and without coparticipation • Dental Insurance: we help you with dental treatment for a better quality of life. • Wellhub Membership: Access a wide range of gyms and training programs.

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