Decision Intelligence. Engineered for Impact.

At OptiML, I help organizations make smarter decisions by combining advanced analytics, machine learning, and optimization. I design and implement models that don't just analyze data — they recommend the best actions based on your goals, trade-offs, and constraints. My work sits at the intersection of data science, ML, business strategy, and mathematical decision-making.

Traditional data science often focuses on describing or predicting outcomes — what happened or what might happen next. My focus is on deciding what to do. That means building integrated ML and optimization models that simulate scenarios, evaluate options, and surface the most effective path forward, even in complex or constrained environments.

I help companies tackle high-stakes, multi-variable decisions where predictive insights and optimization must work hand-in-hand. Typical challenges include:

• Budget allocation and campaign planning using ML-driven forecasts
• Pricing and promotion optimization with demand prediction
• Inventory and supply planning under uncertain demand
• Workforce and territory design informed by predictive models
• Portfolio or resource trade-off modeling combining ML and optimization

These problems require balancing rules, goals, and uncertainty to reach the best actionable outcomes.

I work with decision-makers at:

• Retailers & e-commerce platforms leveraging customer and sales ML models
• Consumer brands (CPG) applying predictive analytics for demand and marketing
• Marketing & media agencies combining ML insights with budget optimization
• Logistics and supply chain operators integrating forecasting and routing
• SaaS & tech companies using ML-powered decision workflows

If you're making complex, data-driven decisions at scale, I can help you structure and solve them.

Both. I run end-to-end projects solo or integrate with existing data and ML teams to bring deep expertise in optimization and decision modeling. Whether you need a short-term specialist or a long-term collaborator, I adapt to your setup and complement your ML initiatives.

I'm pragmatic and flexible — my go-to tools include:

• Optimization: Gurobi, Pyomo, OR-Tools, PuLP
• Machine Learning & Data: Python (scikit-learn, TensorFlow, pandas, NumPy), SQL
• Deployment: Jupyter, Streamlit, FastAPI
• Cloud & Infra: Docker, AWS, Azure

I build solutions that fit your tech stack and can seamlessly integrate ML models with optimization workflows.

Absolutely. I complement internal analytics, ML, or engineering teams by bringing specialized decision modeling and optimization skills — especially useful for strategic planning, trade-off modeling, and integrating ML predictions into prescriptive systems.

Optimization is my core strength, but I also bring experience in:

• Machine learning model development and integration
• Decision architecture & scenario modeling
• Data pipeline design for end-to-end ML and optimization workflows
• Model explainability and stakeholder alignment
• Integrating AI with rule-based decision frameworks

I work at the intersection of ML, operations research, and business logic to drive actionable insights.

Most projects start with incomplete, messy, or imperfect data. I help evaluate what's usable, build model-ready datasets, and develop robust ML and optimization solutions that evolve with your data maturity and quality.