Job Description : Responsibilities :
- Understand Business and product needs and use ML, statistical, and optimization techniques as appropriate to provide solutions to those in a time-bound fashion.
- Communicate and collaborate with business and product teams to have a better understanding of the project so as to be able to drive it within the DS team.
- Get involved in an in-depth exploration of solutions that are to be shared with business and product teams; specifically, build models and scalable custom algorithms for problems, including decision optimisation and predictive modeling.
- Active participation in working with new methods and learning new technologies, in areas including data science and data engineering.
Requirements :
B. Tech, M. Tech, or PhD in CS, Operations Research, or related discipline with professional experience ranging from 5 to 10 years through deployed solutions / projects.The candidate should have taken academic coursework in Operations Research (specifically mathematical optimization).Demonstrated experience in building discrete, linear, nonlinear, or stochastic optimization models is required.Experience with optimization models for supply chain optimization is preferred, but not required.Demonstrated experience in utilizing and tuning commercial optimisation solvers (e. g. CPLEX, Gurobi) and in building custom optimization algorithms (e. g. exact algorithms, metaheuristics, large neighbourhoodsearch, decomposition algorithms, greedy / randomised search) for industry-scale problems is required.
Good grasp on the theory and practice of basic statistical models such as regression or clustering, and general ML algorithms such as tree, Random Forests, SVM, Boosting, Neural Networks, etc. It is not expected that the candidate has actually worked on all these modules.ref : hirist.tech)