Data Scientist - Retail Analytics

Data Scientist - Retail Analytics

- Excellent opportunity to work in a leading customer science company

- Opportunity to be a part of a growing data sciences team

- Opportunity to work with real time transactional data

The Company :

Our client is the leading customer science company working with prestigious retail clients from across the world. The client analysis data and derive insights from millions of shoppers across the globe to create customized shopping experiences.

The Role :

- Based out of Delhi NCR, you will be part of a growing data sciences team.

Some of your key responsibilities will be :

- Research new data science opportunities in areas of prediction, big data to identify new opportunities and give recommendations for future solutions.

- Oversee project delivery for all Data Science related work plans for a Capability that ultimately will help the company grow the loyalty of its client's customers.

- Use advance analytics and machine learning techniques to help the company better understand the business and widen its portfolio

- Ensure all work undergoes a thorough QA process and is error free, resolving any issues or errors to give the best service to the clients.

As a successful applicant you need to have :

- PhD/Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Statistics, Physics, Engineering or related field

- 4 to 7 years of hands on experience in advanced analytics - predictive analytics, statistical analytics, clustering, segmentation

- Proficiency in statistical programming tools (eg. R, SPSS, SAS, Python) is a must

- Specific exposure and hands on experience with machine learning algorithms

- Experience with big data platforms and tools (eg. Hadoop, HDFS, Hive, Pig, Cassandra, Storm) is a must

- An excellent problem solver with research oriented approach

- Ability to engage well with clients

What's on Offer :

- An exciting opportunity to be a part of a growing data sciences team, work on real time transactional data and grow in a meritocratic environment.