• The person will be part of data science team. This person will be working on a close basis with the business analysts and the technology team to deliver the Data Science portion of the project and product.
• Data Science contribution to a project can range between 30% to 80%.
• Day to Day activities will include data exploration to solve a specific problem, researching of methods to be applied as solution, setting up ML process to be applied in context of a specific engagement/ requirement, contributing to building a DS platform, coding the solution, interacting with client on explanations, integration the DS solution with the technology solution, data cleaning and structuring etc.
• Nature of work will depend on stage of a specific engagement, available engagements and individual skill
At least 2-6 years of experience in:
• Machine Learning (including deep learning methods): Algorithm design, analysis and development and performance improvement
o Strong understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering, classification, regression techniques, and recommendation (collaborative filtering) algorithms
o Time Series Analysis
o Optimization techniques and work experience with solvers for MILP and global optimization.
• Data Science
o Good experience in exploratory data analysis and feature design & development
o Experience of applying and evaluating ML algorithms to practical predictive modeling scenarios in various verticals including (but not limited to) FMCG, Media, E-commerce and Hospitality.
• Proficient with programming in Python (must have) & PySpark (good to have). Parallel ML algorithms design and development and usage for maximal performance on multi-core, distributed and/or GPU architectures.
• Must be able to write a production ready code with reusable components and integration into data science platform.
• Strong inclination to write structured code as per prevailing coding standards and best practices.
• Ability to design a data science architecture for repeatability of solutions
• Preparedness to manage whole cycle from data preparation to algorithm design to client presentation at individual level.
• Comfort in working on AWS including managing data science AWS servers
• Team player and good communication and interpersonal skills
• Good experience in Natural Language Processing and its applications (Good to Have)