BeGig is hiring for one of its clients, We are looking for a Data Scientist.
Job Role - Data Scientist.
Work Mode - WFH.
YOE Required - 3+ years.
JD:
Optimization Algorithms:.
- Strong hands-on experience with combinatorial optimization problems, including Knapsack, Bin Packing, and Cutting Stock.
- Deep understanding and experience in developing solutions for multi-dimensional knapsack problems, bin packing with additional constraints, and related issues.
- Proficiency in formulating and solving linear programming (LP), mixed-integer linear programming (MILP), and non-linear optimization problems.
- Experience implementing and fine-tuning heuristic algorithms (e. , greedy algorithms, local search, tabu search).
- Expertise in designing metaheuristic algorithms such as genetic algorithms, simulated annealing, and particle swarm optimization to solve NP-hard problems like knapsack and bin packing.
- Ability to design and analyze algorithms with respect to time and space complexity, especially in P vs NP contexts related to combinatorial optimization.
- Proficiency in using optimization libraries such as Gurobi, CPLEX, OR-Tools, and open-source tools for solving large-scale knapsack and bin packing problems.
- Familiarity with performance optimization and code profiling to handle large-scale optimization tasks efficiently.
- Strong understanding of graph theory, probabilistic algorithms, and data structure optimization.
Machine Learning Integration:.
- Ability to incorporate machine learning approaches for predictive optimization in bin packing and resource allocation.
- Proven track record of applying optimization models to logistics, supply chain management, warehouse management (bin picking), and other real-world optimization problems.
Bonus Skills:.
- Experience in stochastic optimization or reinforcement learning applied to optimization challenges.
- Practical exposure to distributed computing frameworks (e. , Hadoop, Spark) for large-scale optimization
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