{"schemaVersion":"jobsearcher.job.v1","id":"1b1a3f7117ca23ed91eeac35","url":"https://jobsearcher.com/jobs/1b1a3f7117ca23ed91eeac35","canonicalUrl":"https://jobsearcher.com/jobs/1b1a3f7117ca23ed91eeac35","title":"Lead Data Scientist","description":"Role: Lead Data Scientise Work location: Saint Louis, MO – Onsite RoleDuration: 12+ MonthsJob Description:We are seeking a highly skilled Data Scientist Lead to drive enterprise AI/ML strategy, predictive analytics, and intelligent automation initiatives across our large-scale database and cloud ecosystem.This role will lead the design and deployment of advanced machine learning models, AI-driven monitoring solutions, and data science frameworks that enhance performance, reduce risk, optimize costs, and enable data-driven decision-making.The ideal candidate combines strong hands-on data science expertise with leadership capability, strategic thinking, and cross-functional collaboration experience.Key ResponsibilitiesAI/ML Strategy & LeadershipDefine and execute the enterprise AI/ML roadmap aligned with business objectives.Lead development of predictive maintenance, anomaly detection, and capacity forecasting models.Establish best practices for ML lifecycle management (ML Ops).Partner with Engineering, Cloud, Security, and Operations teams to embed AI into core platforms.Advanced Analytics & ModelingDesign, develop, and deploy machine learning models (regression, classification, clustering, time-series forecasting).Implement predictive performance analytics for database infrastructure.Develop cost optimization and workload forecasting models.Leverage Generative AI for automation of operational tasks.Data Engineering & Architecture AlignmentCollaborate with database and cloud architects on scalable data pipelines.Design data ingestion, feature engineering, and model training workflows.Ensure data quality, governance, and compliance standards are met.Team Leadership & MentorshipLead and mentor a team of data scientists and ML engineers.Drive cross-training and upskilling within Database Services.Establish coding standards, documentation, and model validation processes.Provide executive-level reporting and insights.Operationalization & GovernanceDeploy models into production environments with monitoring and retraining pipelines.Implement explainability and model validation frameworks.Ensure AI governance, audit readiness, and ethical AI standards.Required QualificationsBachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or related field.12+ years of experience in data science, analytics, or machine learning.3+ years in a leadership or senior technical role.Strong programming skills in Python (Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch).Experience with SQL and large-scale databases.Expertise in statistical modeling and machine learning algorithms.Experience deploying ML models in cloud environments (AWS, GCP, OCI).Preferred Qualifications:Experience with LLMs, RAG frameworks, or Generative AI applications.Knowledge of ML Ops tools (MLflow, Kubeflow, SageMaker, Vertex AI).Experience in database performance analytics or infrastructure optimization.Familiarity with compliance frameworks (SOX, security governance).Experience in multi-cloud or hybrid cloud environments.Core Competencies:TechnicalPredictive modelingTime-series forecastingAnomaly detectionAI automationData pipeline architectureML OpsLeadershipStrategic thinkingCross-functional collaborationExecutive communicationMentorship and team developmentOwnership & accountabilityBehaviouralData-driven decision makingProblem-solving mindsetContinuous learningInnovation-drivenBusiness ImpactThis role will:Improve infrastructure reliability through predictive insightsReduce operational costs via AI-driven optimizationAccelerate modernization initiativesEnhance compliance and risk managementEnable intelligent automation across database services","company":"Net2Source","rawCompany":"net2source n2s","city":"St Louis","state":"MO","isRemote":false,"isActive":false,"createdAt":"2026-08-13T12:35:25.429Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"11-3021.00","title":"Computer and Information Systems Managers","slug":"computer-and-information-systems-managers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Lead Data Scientist","description":"Role: Lead Data Scientise Work location: Saint Louis, MO – Onsite RoleDuration: 12+ MonthsJob Description:We are seeking a highly skilled Data Scientist Lead to drive enterprise AI/ML strategy, predictive analytics, and intelligent automation initiatives across our large-scale database and cloud ecosystem.This role will lead the design and deployment of advanced machine learning models, AI-driven monitoring solutions, and data science frameworks that enhance performance, reduce risk, optimize costs, and enable data-driven decision-making.The ideal candidate combines strong hands-on data science expertise with leadership capability, strategic thinking, and cross-functional collaboration experience.Key ResponsibilitiesAI/ML Strategy & LeadershipDefine and execute the enterprise AI/ML roadmap aligned with business objectives.Lead development of predictive maintenance, anomaly detection, and capacity forecasting models.Establish best practices for ML lifecycle management (ML Ops).Partner with Engineering, Cloud, Security, and Operations teams to embed AI into core platforms.Advanced Analytics & ModelingDesign, develop, and deploy machine learning models (regression, classification, clustering, time-series forecasting).Implement predictive performance analytics for database infrastructure.Develop cost optimization and workload forecasting models.Leverage Generative AI for automation of operational tasks.Data Engineering & Architecture AlignmentCollaborate with database and cloud architects on scalable data pipelines.Design data ingestion, feature engineering, and model training workflows.Ensure data quality, governance, and compliance standards are met.Team Leadership & MentorshipLead and mentor a team of data scientists and ML engineers.Drive cross-training and upskilling within Database Services.Establish coding standards, documentation, and model validation processes.Provide executive-level reporting and insights.Operationalization & GovernanceDeploy models into production environments with monitoring and retraining pipelines.Implement explainability and model validation frameworks.Ensure AI governance, audit readiness, and ethical AI standards.Required QualificationsBachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or related field.12+ years of experience in data science, analytics, or machine learning.3+ years in a leadership or senior technical role.Strong programming skills in Python (Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch).Experience with SQL and large-scale databases.Expertise in statistical modeling and machine learning algorithms.Experience deploying ML models in cloud environments (AWS, GCP, OCI).Preferred Qualifications:Experience with LLMs, RAG frameworks, or Generative AI applications.Knowledge of ML Ops tools (MLflow, Kubeflow, SageMaker, Vertex AI).Experience in database performance analytics or infrastructure optimization.Familiarity with compliance frameworks (SOX, security governance).Experience in multi-cloud or hybrid cloud environments.Core Competencies:TechnicalPredictive modelingTime-series forecastingAnomaly detectionAI automationData pipeline architectureML OpsLeadershipStrategic thinkingCross-functional collaborationExecutive communicationMentorship and team developmentOwnership & accountabilityBehaviouralData-driven decision makingProblem-solving mindsetContinuous learningInnovation-drivenBusiness ImpactThis role will:Improve infrastructure reliability through predictive insightsReduce operational costs via AI-driven optimizationAccelerate modernization initiativesEnhance compliance and risk managementEnable intelligent automation across database services","datePosted":"2026-08-13T12:35:25.429Z","dateModified":"2026-08-13T12:35:25.429Z","hiringOrganization":{"@type":"Organization","name":"Net2Source","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"St 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