Website: https://www.numbrs.com
Headquarter: Zurich, Switzerland
At Numbrs, our engineers don’t just develop things – we have an impact. We change the way how people are managing their finances by building the best products and services for our users.
Numbrs engineers are innovators, problem-solvers, and hard-workers who are building solutions in big data, mobile technology and much more. We look for professional, highly skilled engineers who evolve, adapt to change and thrive in a fast-paced, value-driven environment.
Join our dedicated technology team that builds massively scalable systems, designs low latency architecture solutions and leverages machine learning technology to turn financial data into action. Want to push the limit of personal finance management? Join Numbrs.
Job Description
- You will be a part of the Data Science team responsible for designing, developing and supporting big data driven predictive models using the latest technologies in machine learning, user pattern recognition, and data modelling.
- The team is responsible to gain new insights which result in the development of product’s features to improve user engagement and experience.
Key Qualifications
- a Bachelor’s or higher degree in technical field of study or equivalent practical experience
- a minimum 5 years of professional experience in Machine Learning
- Experience in pattern recognition, predictive modelling, and statistical analysis
- Strong knowledge in Machine Learning areas such as Neural Networks, Reinforcement Learning, and NLP
- Experience in designing Machine Learning systems at scale
- Experience with Big Data technologies such as Kafka, Spark, and Cassandra
- Fluent with a JVM programming language, ideally Scala.
- Comfort working in a dynamic, research-oriented team with several ongoing concurrent projects
- Excellent troubleshooting and creative problem-solving abilities
- Excellent written and oral communication in English and interpersonal skills
Location: Remote
CLICK HERE TO APPLY
Source: Working Nomads, Numbrs
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