3SC
Website:
3scsolution.com
Job details:
We are looking for a Data Scientist – Supply Chain Optimization with 2+ years of relevant experience in solving complex business problems using mathematical optimization, heuristics, and Python-based solution development.
The ideal candidate should have strong expertise in MILP, heuristic and meta-heuristic techniques, along with a solid understanding of supply chain planning and operational decision-making. This role involves designing practical and scalable optimization solutions for real-world enterprise use cases such as production scheduling, inventory optimization, supply planning, allocation, and logistics optimization.
The candidate should be comfortable translating business requirements into mathematical models, building robust Python-based solutions, and working closely with business, product, and engineering teams to deliver deployable decision science solutions.
Must Have
- 2+ years of relevant experience in Data Science, Operations Research, Optimization, or Decision Science
- Strong hands-on expertise in:
- MILP (Mixed Integer Linear Programming)
- Linear / Integer Programming
- Heuristic algorithms
- Meta-Heuristic techniques (e.g., Genetic Algorithms, Simulated Annealing, Tabu Search, etc.)
- Strong proficiency in Python for model development and solution building
- Experience with one or more optimization frameworks / solvers such as:
- Pyomo
- PuLP
- OR-Tools
- Gurobi / CPLEX (preferred)
- Strong understanding of Supply Chain domain, with experience in one or more of the following areas:
- Supply Planning
- Production Planning / Scheduling
- Inventory Optimization
- Allocation / Replenishment
- Transportation / Logistics Optimization
- Strong problem-solving and analytical thinking skills
- Ability to formulate business problems into:
- Decision variables
- Constraints
- Objective functions
- Scenario / what-if models
- Experience building clean, modular, and maintainable Python solutions suitable for production environments
- Basic understanding of:
- Packaging and deployment of Python applications / services
- Linux / command-line fundamentals
- Docker / containers
- Ability to collaborate effectively with cross-functional teams including business, product, engineering, and data teams
Good to Have
- Experience in real-world supply chain optimization deployments in production or enterprise environments
- Exposure to large-scale combinatorial optimization and performance tuning of optimization models
- Experience with hybrid solution approaches combining exact optimization with heuristics / rule-based methods
- Familiarity with:
- SQL
- Pandas / NumPy
- FastAPI / Flask for model serving
- Git / version control
- Exposure to cloud environments such as AWS / Azure / GCP
- Understanding of simulation, scenario planning, or decision intelligence platforms
- Exposure to Agentic AI / Agentic Systems or AI-assisted decision support concepts, such as:
- Multi-agent workflows
- Tool orchestration
- RAG / context-aware AI systems
- LLM-assisted decision support
- Ability to explain optimization logic, assumptions, and outputs clearly to business stakeholders
Click on Apply to know more.