Build predictive and classification models using data mining techniques
Create algorithms to extract information from large data sets.
Provide relevant solutions and consultancy to business problems
Implement analytics dashboards and visualization at a fast pace
Develop metrics and prototypes that can be used to drive business decisions.
Provide thought--leadership and dependable execution on diverse projects.
Identify emergent trends and opportunities for future client growth and development
Understand business and data requirements to design the Predictive/Machine Learning/Big Data Analytics solutions
Own the responsibility to deliver projects / processes within the stipulated timeline and ensure quality of delivery
Build working relationship with the clients for effective project and process delivery
Dig in and become an expert on numerous industry and country specific datasets.
Provide insight into leading analytic practices, design and lead iterative learning and development cycles, and ultimately produce new and creative analytic solutions that will become part of our core deliverables
Work with cross-functional team members to identify and prioritize actionable, high-impact insights across a variety of core business areas
Design, develop and implement R&D and pre--product prototype solutions and implementations using off the shelf tools (e.g. R, SAS,SPSS), and software (e.g. Python, Java, C/C++, .NET)
Establish scalable, efficient, automated processes for model development, model validation, model implementation and large scale data analysis
Statistical software: Extensive experience working in R/ R Studio/ Revolution R AND Python. Hands on experience in SAS/SPSS is also desirable
Extensive consulting engagements experience
Visualization software: Strong implementation experience in building Shiny application in R AND integrating Google chart API AND building visualization using Python with d3.js.
Completed at least 3 projects using data mining techniques like Support Vector Machine, Artificial Neural Network, Sequence Pattern Mining, etc..
Completed at least 3 projects in Risk modelling, Fraud detection, PD/LGD/EAD modelling.
Strong exposure into Banking, Insurance or Financial Analytics Domainor CPG / Retail domain
Implemented at least 3 parallel processing projects using Hadoop cluster with minimum 500 GB data
Should have excellent business communication and presentation skills
Strong understanding of Advanced Analytics, Predictive Analytics, data warehousing OLAP reporting concepts & strategies
Passion for transforming large amount of data into compelling business insight to facilitate analysis and decision-making
Very good understanding of RDBMs and NoSQL databases
Excellent in writing complex SQL Queries