Senior Data Scientist

Description:

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.g., 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.g., Hadoop, Spark) for large-scale optimization