Senior Data scientist - Optimization Specialist

You are a skilled Principal Data Scientist with 10-13 years of experience in developing enterprise-grade optimization solutions. Your expertise lies in mathematical optimization, Python programming, and bridging the gap between technical and business teams. You will be responsible for leading the design and deployment of scalable optimization engines to solve complex business problems across various domains. Key Responsibilities: - Design & Development: Architect and implement optimization models (LP, MILP, CP, metaheuristics) using solvers like Gurobi, CPLEX, or open-source equivalents. - Platform Building: Lead the design and development of optimization-as-a-service platforms with modular, reusable architecture. - Techno-Functional Role: Translate business requirements into formal optimization problems and provide functional consulting support across domains. - End-to-End Ownership: Manage the full lifecycle from problem formulation, model design, data pipeline integration, to production deployment. - Python Expertise: Build robust, production-grade code with modular design using Python, Pandas, NumPy, Pyomo/Pulp, and APIs (FastAPI/Flask). - Collaboration: Work with business stakeholders, data scientists, and software engineers to ensure solutions are accurate, scalable, and aligned with objectives. - Performance Tuning: Continuously improve model runtime and performance; conduct sensitivity analysis and scenario modeling. - Innovation: Stay abreast of the latest in optimization techniques, frameworks, and tools; proactively suggest enhancements. Required Skills & Qualifications: - Bachelors or Masters in Operations Research, Industrial Engineering, Computer Science, or related fields. - 10-12 years of experience in solving real-world optimization problems. - Deep understanding of mathematical programming (LP/MILP/CP), heuristics/metaheuristics, and stochastic modeling. - Proficiency in Python and experience with relevant libraries (Pyomo, Pulp, OR-Tools, SciPy). - Strong experience building end-to-end platforms or optimization engines deployed in production. - Functional understanding of at least one domain: supply chain, logistics, manufacturing, pricing, scheduling, or workforce planning. - Excellent communication skills - able to interact with technical and business teams effectively. - Experience integrating optimization models into enterprise systems (APIs, cloud deployment, etc.). Preferred Qualifications (if applicable): - Exposure to cloud platforms (AWS, GCP, Azure) and MLOps pipelines. - Familiarity with data visualization (Dash, Plotly, Streamlit) to present optimization results. - Certification or training in operations research or mathematical optimization tools.,