Lead Data Scientist

Description:

Data Scientist Lead

ryze is a digital marketing company to streamline the consumer decision-making process, and connecting customers with industry-leading brands. The networks we create help shoppers make smarter decisions about the products they want to buy.

We are seeking a highly motivated, experienced, passionate Senior Data Scientist to join and lead our team. You’ll have an opportunity to research, design, implement, and evaluate a variety of advanced ML algorithms using the latest technology.

As a data scientist you’ll:

Take on projects end-to-end from business questions all the way to production
Apply cutting-edge solutions while leveraging our expected vast amounts of data
Develop online and scalable models and tools using machine learning and NLP techniques
Work alongside Data Scientist, big data engineers, product managers, and developers from across the organization to solve complex problems
Contribute to continuous learning and knowledge sharing within the data science group, in order to stay ahead of the curve
Lead innovation initiatives and stay in tune with the latest technologies and algorithms
Requirements:
BSc or higher in a quantitative field (math, statistics, computer science, Data Science, etc.).
At least 5 years of experience as a data scientist
Experience solving complex business problems using state of the art algorithms
Strong knowledge of Python and SQL (& ML packages)
Solid background in algorithms, data structures, and programming.
Good understanding of probability and statistics.
Experience in leading data science projects from idea to production in various domains and using various ML solutions.
Ability to mentor others, work in teams, teach and learn from peers
Independent, out of the box thinker.
Experience with working with ML frameworks (e.g., DataBricks, Sagemaker)

advantages:

Experience managing or leading a DS team, preferably in a startup environment.
Experience in ad-tech, specifically in Ad-tech DS (RTB, customer recommendation system, personalisation, etc.).
Experience working on an applied recommendations system solution
Experience in NLP and deep learning techniques
Experience with big-data frameworks (e.g. Spark)