Location: Singapore, Singapore
Thales people architect solutions that support 85 million mainline and suburban passenger journeys, worldwide, every day. Our Rail Signalling and Communication systems are used on metro lines across major cities, and 72,000 kms of route, 52,000 trains per day in 16 countries are controlled by our Traffic Management Systems. Together We deployed the first-ever nationwide ticketing system which processes over 50 million ticketing transactions in 100 cities daily.
Thales in Singapore has been present since 1973, providing state-of-the-art solutions for customers in the aerospace, defence, security and transportation markets. Today, Thales in Singapore employs over 600 people and is home to all regional avionics services, a ground transportation integration centre, and regional innovation hub.
As part of the Software Engineering team building innovative Security solutions for Homeland Security, Smart Cities and Critical Infrastructures, the Data Scientist will:
- Apply Machine Learning (ML) and possibly Deep Learning techniques to a variety of modelling and relevance problems involving our users, Thales Hardware, Thales Software with the end goal of delivering the ML solutions to production.
- REguarly review for performance improvements and decide which ML technologies and algorithms can be used in a production environment.
- Participate in data exploration activities for businesses, uncovering patterns in the data usage.
- Bring the best-in-class practices to the engineering/project team to make sure the data science is maintainable, scalable and debuggable.
- At least 5 years of Data Science experience where you would have understood the process of negotiating and unraveling the nitty gritty details of your customer or user’s datasets with the end goal of building a demonstrable proof-of-concept i.e. PoC or a product.
- Be able to explain the underlying mechanics in addition to the theoretical Machine/Deep Learning model.
- Worked in a squad or guild team setup and understand the Agile processes, ceremonies and appreciate them
- Have good working knowledge of the following:
- One or more programming languages like Python, R, Java & Scala
- Apache Spark and/or Flink
- NoSQL Databases (e.g. ElasticSearch, ScyllaDB)
- Machine Learning and/or Deep Learning algorithms in the realm of supervised, unsupervised, reinforcement not limited to ANN, CNN, RNN, GAN
- Statistical classification domain eg. Logistic Regression, K-NN, Kernel SVM, Naïve Bayes, Decision Tree, Random Forest
- Clustering domain e.g. K-means clustering, hierarchical clustering
- Desirable to have the following:
- A good understanding of applying gradient boosting in regression and classification problems. E.g. XGBoost
- A good repertoire of software tools and programming languages to which you can apply to building a PoC or product.
- Working knowledge in developing visualizations for the PoCs using at least one of d3js, kepler.gl and the like.
- Working knowledge in anomaly detection and outlier detection techniques e.g. DBSCAN, Gaussian Mixture Models.
- Working knowledge of the Machine Learning and Deep Learning toolkits available in OSS, commercial software.
- Good communication skills
- Analytical and problem-solving skills
- Has a continuous learning mindset and learning of new programming paradigms, techniques & practices
At Thales we provide CAREERS and not only jobs. With Thales employing 80,000 employees in 68 countries our mobility policy enables thousands of employees each year to develop their careers at home and abroad, in their existing areas of expertise or by branching out into new fields. Together we believe that embracing flexibility is a smarter way of working. Great journeys start here, apply now!