About the Role: We are looking for people having subject matter expertise in at least one of the following areas: 1. Mathematical optimisation 2. Capacity Planning and Time Series Analysis Our process gives you full ownership over the projects. Ideally, you will be expected to collaborate with the product management team for defining your own problem and drafting a project plan for solving it - from conceptualisation, research, development to production. This job helps you to challenge your analytical knowhow beyond classification, clustering, ranking and regression. Responsibilities:

• You will drive data culture and evangelize use of data science in all possible aspects of business.
• Research and development of bleeding edge OR models and algorithms.
• Discovering new applications of classical OR algorithms like IP, MIP, LP and MLP.
• Iterative improvement of the currently deployed models.
• You get a chance to build OR framework at scale for different aspects of business
• Enhancing existing operations related modules including assignment of tickets to support agents, workflow automation, etc.

About You:

• Excellent problem solving skills, with an ability to communicate even complex ideas in clear manner
• Strong work ethics like sense of collaboration and ownership, result orientation, being a team player
• Proficiency in R, Python, Mathematica, MATLAB or related tools used from data handling to modeling to deployment
• Knowledge of statistical concepts related to data driven design like multivariate testing, DOEs
• Good understanding of applying OR techniques to complex business problems

Requirements:

• MS in Computer Science, Engineering, Statistics, Operations Research or related field with research experience in OR
• Minimum three years of post Masters experience in one of the following domains: (1) Implementation of linear, non
• linear and/or mixed integer programming models for capacity planning (2) Pattern recognition and forecasting using Time Series analyses
• Familiarity with concepts in probability and statistics, including experimental design, predictive modeling, optimization, and causal inference
• Familiarity with concepts in linear algebra, including matrix manipulation, Gaussian Elimination and Eigenvalue problems
• Deep knowledge in the theory of convex optimization, first-order iterative optimization algorithms (gradient descent, conjugate gradients etc.), and mathematical programming (IP, MIP, LP, MLP, etc.)
• A strong sense of connecting technical work to product impacts
• Expert knowledge of a statistical computing language such as R, Python, Mathematica or MATLAB.
• Excellent written and verbal technical communication skills
• Familiarity with a scripting language and/or shell scripting

Nice-to-haves:

• Preferred: Ph.D./Post-Doc in Computer Science, Engineering, Statistics, Operations Research or other relevant technical field
• Preferred: Experience with large-scale distributed systems
• Preferred: Experience with tools in the Hadoop ecosystem such as Hive, Pig, or Spark
• Preferred: Knowledge of functional programming languages like Lisp, Haskell, Clojure
• Past experience in Machine Learning
• Past experience in Customer Services/Contact Centers domain