Lead Data Scientist

Role: Lead Data Scientise Work location: Saint Louis, MO – Onsite Role Duration: 12+ Months Job 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 Responsibilities AI/ML Strategy & Leadership • Define 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 & Modeling • Design, 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 Alignment • Collaborate 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 & Mentorship • Lead 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 & Governance • Deploy 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 Qualifications • Bachelor’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: Technical • Predictive modeling • Time-series forecasting • Anomaly detection • AI automation • Data pipeline architecture • ML Ops Leadership • Strategic thinking • Cross-functional collaboration • Executive communication • Mentorship and team development • Ownership & accountability Behavioural • Data-driven decision making • Problem-solving mindset • Continuous learning • Innovation-driven Business Impact This role will: • Improve infrastructure reliability through predictive insights • Reduce operational costs via AI-driven optimization • Accelerate modernization initiatives • Enhance compliance and risk management • Enable intelligent automation across database services