Machine Learning Guru  

We’re a world-leading smart mobility SaaS tech company with over 1,200,000 subscribers across 23 countries. Our teams are collaborative, vibrant and fast-growing, and all team members are empowered with the freedom to influence our products and technology.

• Are you curious, innovative and passionate?
• Do you take ownership, embrace challenges, and love problem-solving?

We’re looking for a Data Scientist (Machine Learning) who will help us continue to build industry disruptive tech products and revolutionise the way our customers use technology.

You want to

• Conceptualize and develop machine learning models
• Develop and implement optimization algorithms
• Develop cutting edge differentiated capabilities in spatial and temporal data management to establish a competitive edge.
• Implement and put models into production.
• Constructing solution concepts from insights using familiar or unfamiliar data sources or complete or partial data.

• Minimum 2 years of relevant experience in one or more of the following:
• Developing machine learning models, signal processing, large scale optimization
• Ph.D., Master’s or an outstanding Bachelors in Computer Science, Electrical/Computer Engineering, Mathematics/Statistics, Operations Research, Industrial & Systems Engineering, or related technical disciplines.
• Strong fundamentals in at least one of the following: ML, optimization or simulation, Signal Processing with familiarity of the others.
• Proficient in Python; and strong working knowledge in RDBMS such as PostgresQL or NoSQL
• Self-motivated and independent learner who is willing to share knowledge with the team.
• Efficient and detail-oriented time manager who thrives in a dynamic and fast-paced working environment
• Creative thinking backed by strong analytical and problem-solving skills.
• Strong teamwork, co-ordination, and planning, self-driven, and ability to work at pace in a dynamic organization.
• Plus: programming skills in Java and Scala, experience in functional programming is preferred