Nexite is a leading startup, revolutionizing retail IoT. We are developing a platform that merges the physical and digital retail spaces. Our innovative platform is based on cutting edge battery-less BLE tags that communicate with a cloud platform through an in-store wireless access network. Using our data and cloud platform, we can provide retailers with previously unattainable insights and analytics and at the same time vastly improve the customer experience.

We are hiring a Data Scientist to join our core Data Science & Data cross-functional team, which includes Data Scientists, ML Engineers, Data Engineers, and Data Analysts.

As a Data Scientist, you will work on a range of challenges across different ML domains and use cases, such as recommendation systems, time series analysis, signal processing, forecasting, space optimization, clustering and more, using vast amounts of data constantly transmitted from our clients' locations, leveraging Nexite's cutting edge technology.

Responsibilities:

• Work with a huge scale of data that is constantly transmitted from our clients locations.
• Research and implement state of the art methods into various use cases
• Work on projects from business questions to delivering validated working models.
• Work closely with product managers, data engineers & other stakeholders. be the focal point of your projects, identify new opportunities & initiatives.
• Identify and propose algorithmic solutions for various initiatives.
  
  

Requirements:

• 4+ years of data science knowledge and hands-on industrial experience.
• Strong programming skills in Python, PySpark, SQL.
• Master’s Degree or above in Statistics/ Computer Science/ Mathematics or relevant background/experience.
• Good understanding of probability and statistics.
• Deep understanding of Machine Learning methodologies, algorithms and models.
• Deep Learning experience - an advantage.
• Ability to work as an individual contributor and as part of a team
  
  

Would be nice:

• Hands-on experience in data engineering, working with big data frameworks like Spark/Hadoop