Data ScientistLocation: Cambridge, MAPosition Type: Contract (06/01/2026 – 12/31/2026) Rate: DOEResponsibilitiesPerform advanced data analysis, visualization, and statistical modeling.Apply Bayesian experimental design techniques.Develop optimization and simulation solutions including:Constrained optimizationMachine learningMonte Carlo simulationsSolve manufacturing challenges such as:Schedule optimizationBatch generationPartner with stakeholders across:Data acquisitionModelingValidationDeploymentMonitoringCollaborate with:Data scientistsEngineersStatisticiansManufacturing teamsImplement best practices for:ScalabilityReproducibilitySoftware engineeringPresent analytical insights to technical and non-technical audiences.Integrate Generative AI capabilities into workflows and experimentation.Required QualificationsPhD in a quantitative STEM field with 0–2 years' experience, ORMaster's degree with 5–8 years relevant experience.Experience delivering data science projects on scientific/engineering datasets.Strong communication and collaboration skills.Expertise in:PythonPandasJupyterscikit-learnMachine learning librariesFamiliarity with:AWSDockerGitPostgreSQLExperience handling large and unstructured datasets.Ability to manage multiple projects in dynamic environments.English proficiency required.Optimization and bioinformatics experience preferred.Key ResponsibilitiesBuild and tune supervised and unsupervised ML models for anomaly detection.Monitor real-time data streams and system logs.Analyze complex datasets to identify root causes of anomalies.Optimize alert systems to minimize false positives.Develop automated pipelines for:Data qualitySecurityDetection systemsWork closely with product management, IT, and data engineering teams.Apply:Statistical analysisData miningFeature engineering techniques.