Data Scientist - R/SAS Programming - Retail eCommerce

We are looking for a Strong Data scientist for online arm of indian Retail conglomerate.

What is that we are looking for :

- Never ending love for data and thereby assess the importance of every data point that would help the business grow

- Out of the box thought process to overcome the traditional analytics practice and emphasize on Research & development to build world class solutions to drive Customer-Purchase story

- Hunger to learn new tools and technologies on the go to develop best practices in Business Intelligence implementation and ease of doing data mining

- A leader and a team player who could disrupt the traditional ecommerce recommendation system by collaborating with different teams and creating a unique, flawless, ever improving, purchase persuasive recommendation engine that increases customer satisfaction and Loyalty

- Sound understanding of the Retail and Ecommerce business theories with a good touch of statistics to back these and convert them into more revenues

- A beautiful mind that is able to unlock the true potential of the enormous structured and unstructured data being captured using statistical concepts and building their own set of machine learning algorithms

What are the skills that is a must to have :

- Min 3 years of experience in the ecommerce sector plus 2 years in the retail apparel sector (Preferrable)

- Good with SQL, MS-Excel and PowerPoint

- Strong hold on either R, SAS programming

- Great understanding of Statistical Concepts and modelling techniques

- Hands on experience in web analytics tools such as Google analytics

- Should have been part of various Kaggle/Analytics Vidya events and built awesome tuning algorithms (should have been in the Top 10 percentile)

Why should you join us :

- If you love to get your hands dirty working on huge data sets, then there is no better place to go

- If you would love to revolutionize the Ecommerce-Mcommerce-Retail union, then join the party

- If you are ready to make mistakes, then come to us to make a lot of mistakes and then learn from them and implement the learnings

- If you get a high looking at numbers, then we have plenty of them in stock