Data Scientist; Domain – Marketing

About the role:

Target Data Sciences is offering an exciting opportunity to solve state of the art problems in retail. The opportunity will allow you to analyse large and varied data sets, build models on transactional behaviour and write algorithms to improve guest (customer) experience. In this role, you will have access to the best tech stack in retail along with working with a set of passionate co-workers committed to creating next gen Marketing capabilities. You can expect to be involved in:

• Learning and working on different aspects of personalisation of guest offers
• Learning about the complex world of digital ad – tech and supporting Target’s advertising business by bringing state of art ad relevancy to life
• Creating large and automated data pipelines and documenting methods and outputs
• Exploring different approaches to solve a problem, testing the solutions, and reporting the results
• Implementing large scale and automated models and create dashboard to capture relevant metrics and determine errors

Example problem statements:

• Given a category (toys, baby, apparels, etc.) campaign, what is optimal offer variations and who should get the offers?
• Given digital ad variations how do we optimize ad impressions?
• How do we set prices for digital product ad slots to achieve higher revenue?
• How to systematically scale and automate such decisions impacting millions of guests?

Expected skills:

• Data wrangling and pipelining skills using HiveQL, Python, Spark
• Ability to write modular code and data pipelines which can be automated and scaled
• Good programming skills in Python/ Scala/ Java
• Ability to work with a team(s) to drive the work in a collaborative environment

Preferred Educational background:

• Engineering graduates from reputed institutes with proficiency in coding
• MTech or MS (Statistics, Economics, CS, Mathematics)

Preferred domain experience: in enabling data driven solutions in marketing, marketing campaign management, digital media, measuring RoI on customer marketing campaigns, customer personalisation, behavioural models.