Our Client is 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
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
Requirements
- 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 and accountability
Behavioral:
- Data driven decision making
- Problem solving mindset
- Continuous learning
- Innovation-driven
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Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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