Data Scientist – RF/Acoustics Signal Processing

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Logo of Cutsforth Inc.

Cutsforth Inc.

11 - 50 funcionários

⚡ Energia

🔧 Hardware

🏢 Corporativo

Energy • Hardware • Enterprise

A Cutsforth Inc. é uma empresa especializada em soluções de engenharia inovadoras para melhorar o desempenho e a confiabilidade de ativos industriais, particularmente no setor de geração de energia. Eles oferecem uma gama de produtos e serviços, incluindo a plataforma de monitoramento de ativos online InsightCM™, suportes de escova removíveis EASYchange®, sistemas de aterramento de eixos e vários serviços de monitoramento e confiabilidade. Com mais de 30 anos de experiência, a Cutsforth é conhecida por seu excepcional atendimento ao cliente e expertise na indústria, fornecendo soluções que ajudam as empresas a melhorar a disponibilidade, confiabilidade e custo-eficiência de suas operações.

Descrição

• Applies data science and machine learning to the analysis of radio frequency and acoustic signals, transforming raw time-series sensor data into actionable diagnostics and predictive insights. • Partners with engineering and domain experts to design and deploy production-grade signal processing and ML solutions across industrial, communications, and defense-adjacent applications. • Operates effectively in ambiguous problem spaces where signal quality, environmental noise, and domain constraints require both technical rigor and adaptive thinking. • Design and develop signal processing pipelines and machine learning models that operate on RF, acoustic, and time-series sensor data, including beamforming, BSS, spectral subtraction, matched filtering, wavelet decomposition, and time-frequency analysis techniques. • Evaluate algorithm performance using both objective metrics and subjective measures, including integration with speech recognition engines where applicable. • Perform exploratory data analysis, feature engineering, and signal feature extraction on raw demodulated RF and acoustic data to surface patterns and anomalies. • Analyze and interpret signals from various electrical asset monitoring systems utilizing RF, acoustic, and signal processing expertise to support fault isolation and anomaly detection. • Use asset monitoring sensor data as measurement to characterize and validate signal data. • Apply data-driven signal processing methods to characterize and isolate faults at the subsystem, component, and LRU level — identifying root causes from spectral, RF, and acoustic sensor data in complex industrial systems. • Contribute to end-to-end ML workflows including data ingestion, model training, inference, and monitoring for drift and degradation in live environments. • Collaborate with engineering, product, and domain SMEs to translate operational challenges into well-scoped data science solutions. • Communicate findings, model performance, and business value clearly through visualizations, written documentation, and presentations to technical and non-technical stakeholders. • Explore and evaluate emerging signal processing and AI techniques, recommending production incorporation where appropriate.

🎯 Requisitos

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, or a closely related engineering discipline required. • 5+ years of professional experience in data science, machine learning, or applied signal processing, with demonstrated work on RF, acoustic, ultrasonic, or communications signal data. • Direct industry experience in one or more of: Aerospace, Telecommunications, Military/Defense communications, Industrial Acoustics, or RF/Electronic Systems. • Hands-on experience with time-series and signal processing techniques, including spectral analysis, filtering, and feature extraction from raw sensor or radio data. • Proficiency in Python, including scientific computing libraries (NumPy, SciPy, pandas) and ML frameworks (scikit-learn, PyTorch, or TensorFlow). • Demonstrated use of RF measurement and analysis workflows, including use of spectrum analyzers, network analyzers, signal generators, and oscilloscopes in a professional engineering context. • Strong analytical and problem-solving skills with the capacity to work through ambiguous or data-sparse problem spaces. • Excellent written and verbal communication skills; ability to present technical findings to non-technical audiences. • Knowledge of Electromagnetic Compliance techniques.

🏖️ Benefícios

• Paid Time Off • Medical, Vision, Dental Insurance • Health Savings Account with Employer contributions • 401(k) with Employer match • Short-term & Long-term Disability Coverage • Accidental Death & Dismemberment Coverage • Life Insurance Coverage • Eight paid holidays per year

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