Decision Intelligence Architect

We are seeking a highly experienced Senior Decision Intelligence Architect to lead the design and implementation of enterprise decision intelligence solutions. This role combines expertise in decision science, machine learning, optimization, and business strategy to build intelligent decision-making systems that improve operational efficiency and business outcomes. The ideal candidate will have strong technical depth in predictive analytics, optimization techniques, and decision automation, along with the ability to translate complex business challenges into scalable decision frameworks., * Design and implement enterprise decision intelligence frameworks to solve complex business problems.

• Develop decision models using decision trees, causal inference, optimization algorithms, and simulation techniques.
• Build predictive and prescriptive analytics solutions using machine learning and statistical modeling.
• Apply Bayesian methods, reinforcement learning, and uncertainty quantification to optimize business decisions.
• Architect real-time decisioning systems that integrate machine learning models into operational workflows.
• Design and manage scalable decision engines, business rules platforms, and intelligent automation solutions.
• Collaborate with business stakeholders to identify high-value decision opportunities and convert them into analytical solutions.
• Develop optimization models using linear programming, integer programming, and mixed-integer optimization techniques.
• Build simulation models including Monte Carlo simulations and agent-based modeling for scenario analysis.
• Lead deployment and lifecycle management of decision models using MLOps best practices.
• Mentor data scientists, machine learning engineers, and analytics teams on decision intelligence methodologies.
• Drive enterprise adoption of decision intelligence and influence strategic initiatives across business units.
• Communicate analytical findings and recommendations effectively to executive leadership., * Python
• R
• Decision Management Platforms (Pega, IBM ODM)
• Graph Databases (Neo4j or similar)
• SQL
• MLOps
• Git
• Docker
• Kubernetes
• Cloud Platforms (AWS, Azure, or Google Cloud Platform)

Leadership & Strategy

• Decision Intelligence Strategy
• Executive Stakeholder Management
• Business Transformation
• Team Leadership & Mentoring
• Cross-Functional Collaboration
• Strategic Roadmap Development
• Change Management
• Executive Communication

• Decision Trees
• Causal Inference
• Linear Programming
• Integer Programming
• Mixed Integer Optimization
• Monte Carlo Simulation
• Agent-Based Modeling
• Decision Analysis
• Prescriptive Analytics

Machine Learning & Statistical Foundations

• Predictive Modeling
• Bayesian Statistics
• Reinforcement Learning
• Statistical Modeling
• Probability Theory
• Uncertainty Quantification
• Experimental Design
• Time Series Forecasting

Systems & Architecture

• Decision Engine Design
• Rules-Based Systems
• Real-Time Decisioning
• Business Rules Management Systems (BRMS)
• Decision Automation
• Workflow Integration
• API-Based Architecture
• Enterprise Solution Architecture, * Bachelor’’s or Master’’s degree in Computer Science, Data Science, Statistics, Operations Research, Applied Mathematics, Engineering, or a related field.
• 10+ years of experience in Decision Science, Data Science, Machine Learning, Operations Research, or Decision Intelligence.
• Strong expertise in optimization techniques, predictive modeling, and statistical analysis.
• Experience designing enterprise decision management systems and intelligent decision engines.
• Hands-on experience with Python or R for analytical modeling.
• Experience with decision management platforms such as Pega or IBM ODM is highly preferred.
• Experience deploying production-grade machine learning and decision models using MLOps practices.
• Proven ability to lead cross-functional teams and influence executive stakeholders.