- Understanding of machine learning, deep learning, data mining, algorithmic foundations of optimization.
- Experience with machine learning framework (scikit-learn, Spark MLlib etc).
- Proficient in one or more of the following programming languages: Python, R, Scala.
- Experience in building ML models at scale, using real-time big data pipelines on platforms such as Spark/MapReduce.
- Familiar with noSQL, postGIS, stream processing and distributed computing platforms.
- Self-motivated, independent learner, and willing to share knowledge with team members.
- Detail-oriented and efficient time manager in a dynamic and dynamic working environment.
- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- This is a newly created role with plenty of opportunity for more responsibility in the future - Bykea’s Data Scientist will work on some of the most challenging and fascinating problems in transport, logistics, economics, and the space around. You will apply deep learning, geospatial data mining, simulation, forecasting, scheduling, optimization, and many other advanced techniques on our huge datasets to push our business metrics to their bounds, directly and indirectly.
- Sample of problems the Data Science Department solve - Intelligent allocation, machine/deep learning - based predictions (all sorts!), Dynamic pricing, Supply/demand forecasting and positioning, Incentives and promotions optimization, Ride matching, on-demand routing and scheduling, Multi-modal transport, Geospatial data mining, etc.
- You will build algorithms and models to match passenger and driver, to predict time of arrival, to predict when a driver will churn (i.e. stop driving for Bykea) etc. If you enjoy predictions and algorithms, let's have a chat!
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