This is an exciting opportunity to be part of a brilliant team in a fast-paced, collaborative environment. You will have the chance to influence and shape our Product, Technology and Data Science strategy while working with billions of data points by developing machine learning models to solve real-world, measurable problems!
CitySwift is a Cloud-native, specialist data engine for modern bus networks. We optimise urban bus networks using Big Data and Analytics. Ultimately, we improve the reliability of services while simultaneously reducing Operator costs, resulting in a win-win for both passengers and operators!
Our Company Values
- Be Open & Honest
- Take Ownership & Finish it!
- Think like a Customer
- Alright is not OK!
- Be up for the challenge.
What You’ll Do:
- Liaise between R&D data scientists and software engineers to prepare and implement productionisation of predictive and statistical models.
- Develop scalable feature engineering pipelines and from a multitude of data sources at varying frequencies.
- Facilitate best implementation and usage of model outputs be it batch or real time predictions.
- Work closely with data scientists to develop continuous evaluation and performance degradation reporting.
What you bring:
- Proven experience productionising models using cloud computing and serving predictions in a variety of manors.
- A solid understanding of machine learning model capabilities and requirements to implement a scalable solution.
- Experience of pipe-lining technologies for data large scale data curation such as Apache beam.
- Experience using TensorFlow Transform for preprocessing at scale.
- Experience of varying hosted and cloud compute for model training and predicting.
- Experience of hosted models for on demand prediction generation.
It would be great if you have:
- Experience with multiple neural networks architectures and approaches.
- Knowledge of model explain-ability and automated evaluation.
- Experience with GIS software/analysis tools as well as routing algorithms with a focus on machine learning integration.