Data Scientist

at  Thales

Location: Singapore, Singapore
In fast changing markets, customers worldwide rely on Thales. Thales is a business where brilliant people from all over the world come together to share ideas and inspire each other. In aerospace, transportation, defence, security and space, our architects design innovative solutions that make our tomorrow’s possible.
Thales established its presence in Singapore in 1973 to support the expansion of aerospace-related activities in the Asia-Pacific region. Throughout the last four decades, the company grew from strength to strength and is today involved in the primary businesses of Aerospace (including Air Traffic Management), Defence & Security, Ground Transportation and Digital Identity & Security. Thales today employs over 2,100 people in Singapore across all its business areas.

ROLE DESCRIPTION SUMMARY

As a Data Scientist in the Digital Factory, you would be expected to partake in solving machine/deep-learning problems in various domains (e.g. Avionic Systems, Radar Systems, Underwater Systems) with varying degrees of complexity. You should also have experience in presenting the results of experiments conducted, failures and successes towards key stakeholders in an understandable fashion. You should be someone whom has an advanced degree in Mathematics and/or Statistics. You should also have programming experience and understand how to create business savvy visualizations for your key stakeholders. You should also be someone whom has past experience coaching lesser experienced data science professionals. You should be someone whom has past experience in fine-tuning machine learning algorithms in production environments. You should be someone whom is aware that there is a lot you do not know but willing to acquire and validate knowledge; is not emotionally attached to share your failures and subsequent learnings. You should be someone whom is willing to partake in the day to day engineering activities of your team and factory.

KEY ACTIVITIES AND RESPONSIBILITIES

As a Data Scientist, you are accountable for:

• You will apply machine learning 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 AI solutions to production.
• You will participate in the engineering life-cycle at Thales Digital Factory, including daily scrum, sprint reviews, sprint retrospectives, community of practices etc
• You will have to review, regularly, for performance improvements and decide which AI technologies and algorithms can be used in a production environment
• You will partake in data exploration activities for businesses, uncovering patterns in the data usage.
• Extracting actionable insights from diverse data sources through data mining techniques
• You will design and apply algorithms to identify key features, build, and fine-tune models
• You will work closely with data engineer in implementing preprocessing of both structured and unstructured data
• You will evaluate and identify relevant datasets and create data dictionaries when applicable
• You will be handling data processing, cleansing, and validation to ensure its suitability for analysis
• You will deliver clear and concise presentations of analytical findings with stakeholders
• You will bring the best-in-class practices to the MVP team to make sure the data science is maintainable, scalable and debuggable

TO BE SUCCESSFUL IN YOUR ROLE, YOU WILL HAVE DEMONSTRATED AND/OR ACQUIRED THE FOLLOWING KNOWLEDGE AND EXPERIENCE:

• 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.
• You should have a good repertoire of software tools and programming languages to which you can apply to building a PoC.
• You should have good working knowledge about Machine Learning and/or Deep Learning algorithms in the realm of supervised, unsupervised, reinforcement not limited to ANN, CNN, RNN, GAN.
• You should have good working knowledge in statistical classification domain eg. Logistic Regression, K-nn, Kernel SVM, Naïve Bayes, Decision Tree, Random Forest.
• You should have good working knowledge in clustering domain e.g. K-means clustering, hierarchical clustering
• You should have a good understanding of applying gradient boosting in regression and classification problems. E.g. XGBoost
• You should have good working knowledge in anomaly detection and outlier detection techniques e.g. DBSCAN, Gaussian Mixture Models.
• You should have deep understanding and experience with large language modeling techniques, such as GPT, BERT, or Transformer-based architectures.
• You should be familiar with large language modeling frameworks like OpenAI’s GPT, Hugging Face’s Transformers, or Google’s BERT.
• You should have knowledge of natural language processing (NLP) concepts and techniques, such as tokenization, word embeddings, and sequence modeling.
• You should have proficiency in reinforcement learning algorithms and concepts. This includes understanding the basics of Markov Decision Processes, Q-learning, policy gradients, and value iteration.
• You would have working knowledge of one or more programming languages like C & Python and you should be able to explain the underlying mechanics in addition to the theoretical Machine/Deep Learning model.
• You would have good working knowledge of the Machine Learning and Deep Learning toolkits available in OSS, commercial software.
• Worked in a squad or guild team setup and understand the agile processes, ceremonies and appreciates them
• Has a continuous learning mindset and learning of new programming paradigms, techniques & practices
• Open, strong communicator who communicates effectively across teams, locations and cultures, in-person and virtually
• Courage of convictions with a high degree of humility. Embraces constructive feedback and is resilient
  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