Data Scientist

Há 4 dias

Ituiutaba, Brasil Vista Applied Solutions Group Inc Tempo inteiro

Job Summary:Client is seeking a hands-on Applied ML / Application Engineer to support a global manufacturing organization focused on process chemical manufacturing. This is a critical role that sits at the intersection of data science, machine learning, and manufacturing operations. The ideal candidate understands how to apply data science principles in a production environment and can work closely with both business and operational teams to drive value through anomaly detection, yield optimization, and process improvements.Note: Preference is local Curitiba Brazil for sporadic onsite visits. Responsibilities:Collaborate with business stakeholders, manufacturing engineers, and data teams to translate operational challenges into ML-driven solutions.Utilize existing ML models (and adjust where necessary) to support yield improvement, root-cause analysis, and anomaly detection.Understand contextual asset and process data to build digital threads across manufacturing workflows.Act as a bridge between the manufacturing floor and data/ML teams—communicating technical concepts in a way that's digestible to non-technical stakeholders.Work with data from multiple systems including MES, QMS, LIMS, process historians, and time series platforms.Learn and leverage Twin Thread platform to operationalize and deploy ML models.Collaborate with engineering teams on data ingestion and pipeline development when necessary.Support visualization efforts that convey model insights and drive data-driven decision making.Ensure models align with existing ISA-95 / ISA-88 architectures across batch and continuous processing environments.Experience:3–7 years' experience in applied ML / data science / data engineering roles, preferably in a process manufacturing or chemical manufacturing setting.Background in chemical engineering, industrial automation, or manufacturing systems.Knowledge of ISA-95 / ISA-88 standardsStrong understanding of manufacturing operations, particularly continuous and batch processing systems.Proven experience with anomaly detection, predictive maintenance, or yield optimization in an industrial context.Familiarity with time-series data, process historians, QMS, LIMS, MES, and related systems.Comfortable interacting with both business stakeholders and hands-on operational staff; strong communication and stakeholder engagement skills.Experience working with Twin Thread or similar industrial AI platforms a strong plus (willingness to learn is acceptable).Experience with data visualization tools and storytelling with data.Familiarity with cloud platforms and common ML libraries (e.g., scikit-learn, Py Torch, Tensor Flow) is beneficial but not essential.Nice to Have:Experience with model deployment in production systems.Exposure to digital twin or digital thread concepts.English and Portuguese speaking (they have translators if not)

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