
1 - 10 funcionários
Fundada em 1999
🤝 B2B
☁️ SaaS
Technology • B2B • SaaS
A NOVA Corporation é uma fornecedora líder de soluções tecnológicas avançadas, voltadas para aumentar a eficiência e a produtividade em diversos setores. Com forte foco em inovação, a NOVA Corporation desenvolve produtos de software e hardware de ponta que atendem tanto aos mercados corporativo quanto consumidor. A missão da empresa é capacitar organizações com as ferramentas de que precisam para ter sucesso em um cenário digital em rápida transformação.
🕒 Dezembro 5, 2025
🗣️🇺🇸🇬🇧 Inglês obrigatório
Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

1 - 10 funcionários
Fundada em 1999
🤝 B2B
☁️ SaaS
Technology • B2B • SaaS
A NOVA Corporation é uma fornecedora líder de soluções tecnológicas avançadas, voltadas para aumentar a eficiência e a produtividade em diversos setores. Com forte foco em inovação, a NOVA Corporation desenvolve produtos de software e hardware de ponta que atendem tanto aos mercados corporativo quanto consumidor. A missão da empresa é capacitar organizações com as ferramentas de que precisam para ter sucesso em um cenário digital em rápida transformação.
• Lead the end-to-end lifecycle of machine learning and statistical models, from problem framing and data acquisition through deployment, monitoring, and retirement. • Design and implement models using causal inference and Bayesian methods to support high-impact operational and strategic decisions. • Develop and maintain model risk management practices, including validation, back-testing, performance thresholds, and issue remediation. • Create and maintain model cards and other documentation that clearly describe model purpose, assumptions, limitations, performance, and governance controls. • Embed ethical AI principles into model design and usage, including fairness, transparency, explainability, and human-in-the-loop oversight. • Architect and scale analytical solutions on DoD data fabrics and cloud environments, collaborating with cloud architects and engineering teams. • Define and track model and analytics performance against AQLs and QASP metrics; proactively recommend improvements to meet or exceed targets. • Partner with security, infrastructure, and operations teams to ensure models comply with cybersecurity, data protection, and configuration management policies. • Provide technical leadership and mentorship to junior data scientists and analysts, reviewing work products and promoting best practices. • Prepare and deliver briefings, dashboards, and written reports that distill complex analytics into clear, actionable insights for senior leaders. • Support proposal and capture efforts by contributing data science subject matter expertise and solution concepts as needed.
• Active Secret clearance; must be able to obtain and maintain a Top Secret clearance if required by the customer. • 9–12 years of progressive experience in data science, machine learning, statistics, or a closely related field, including support to DoD or other U.S. government customers. • Master’s degree (MS) in Data Science, Computer Science, Statistics, Electrical Engineering, or a closely related discipline (required). • PhD in one of these fields (preferred). • Demonstrated hands-on expertise with causal inference and Bayesian methods applied to real-world decision problems. • Proven experience implementing and maintaining model risk management frameworks in production environments. • Experience generating model cards and other structured documentation for models, including performance metrics and limitations. • Strong background in ethical AI concepts and techniques, including bias detection/mitigation and responsible AI governance. • Hands-on experience deploying and scaling models on cloud platforms and/or DoD data fabrics (e.g., enterprise data platforms, secure enclaves). • Proficiency in at least one major programming language used for data science (e.g., Python, R) and modern ML tooling (e.g., scikit-learn, PyTorch, TensorFlow, or equivalent). • Strong communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.
• Health insurance • Flexible work arrangements • Professional development
Candidatar-se🕒 Novembro 25, 2025
Data Scientist Specialist developing, validating, and implementing Machine Learning solutions. Collaborating with cross-functional teams to drive AI/ML projects effectively and efficiently.
🗣️🇧🇷🇵🇹 Português obrigatório
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