Profile Description -
Formulate and solve Operational Research problems aimed at optimizing the company's supply chain network and automating daily operations.
Client Details -
The client is India's largest and most profitable fulfillment company for digital commerce.
- Collaborate with cross-functional teams including but not limited to Engineering, Products, Operations, Sales, Marketing, Security, Customer Service, etc. to breakdown complex business problems and recommend data science products
- Translate business processes to mathematical models
- Take ownership of a project and be able to work independently with little supervision
- Formulate and solve Operational Research problems aimed at optimizing the company's supply chain network and automating daily operations
- Use statistical methods for analysing large datasets
- Code system prototypes in an object oriented language or scripting/modeling language
- Disseminate original research in peer reviewed journals and conferences
- Degree (B.Tech, MS, PhD or equivalent) in Computer Science, Mathematics, Operational Research, Statistics or Natural Sciences
- 1-7 years of work experience in data science and statistical modeling for DS, 3+ for Sr. DS
- A very clear understanding of probability and statistics, analytical approach to problem-solving, and capability to think critically on a diverse array of problems
- Practical and Theoretical knowledge of OR Tools: Mathematical Programming (Linear/Non-linear techniques), Graph Theory, Simulation, Convex Optimisation, Transportation Problem, Vehicle Routing Problem, Facility Location Problem, Queuing Theory, Inventory Management, Forecasting Techniques, etc.
- Knowledge about meta-heuristics like Genetic Algorithm, Tabu Search, Simulated Annealing, etc would be beneficial.
- Understanding of Mixed Integer Programming techniques to leverage commercially available libraries such as CPLEX, COIN-OR, Google OR-Tools, R and adapt them as required
- Familiarity with statistical methods such as hypothesis testing, forecasting, time series analysis, etc - gained through work experience or graduate level education
- Expertise in at least one of the following languages: Python, Java, C++
- Experience with relational databases NoSQL databases such as MongoDB, Elastic Search, Redis or any graph database
- Experience in handling geospatial data such as PostGIS will be appreciated
- Skilled at data visualization and presentation
- Good communication skills with both technical and business people
- Experience with big data tools like Spark, Hadoop is a plus
- Publications in peer-reviewed journals will count in your favor
- Most importantly, an inquisitive mind, an ability for self-learning and abstraction along with a risk appetite for experimentation and failure