Data Scientist

Thales
Singapore
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 3-5 yearsEducation: bachelorsSkills: ["Learning agility","Flexibility","Pro-activity","Agile teamwork","User engagement"]

Design and conduct exploratory data analysis for air traffic optimization, then build and deploy end-to-end machine learning solutions. Develop real-time classification, regression, and sequence prediction models, including transformer-based architectures, and reinforcement learning agents for simulated and real-world environments. Create and optimize RAG pipelines, evaluate LLM outputs for hallucination and groundedness, and build domain-specific benchmarks. Operationalize models with MLOps, APIs, Docker/Kubernetes, and monitoring for production drift.

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FursaFursa
Thales
Thales
1 month ago

Data Scientist

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 46 minutes agoStatus: Live
Reposted: similar role first listed 7 months ago

Job Summary

Design and conduct exploratory data analysis for air traffic optimization, then build and deploy end-to-end machine learning solutions. Develop real-time classification, regression, and sequence prediction models, including transformer-based architectures, and reinforcement learning agents for simulated and real-world environments. Create and optimize RAG pipelines, evaluate LLM outputs for hallucination and groundedness, and build domain-specific benchmarks. Operationalize models with MLOps, APIs, Docker/Kubernetes, and monitoring for production drift.
Location: Singapore
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and conduct exploratory data analysis to uncover patterns and opportunities for air traffic optimization.
  • •Design, develop, and deploy ML models for real-time classification, regression, and sequence prediction, including transformer-based approaches.
  • •Develop reinforcement learning agents and apply them to simulated and real-world environments.
  • •Build and optimize RAG pipelines using domain documentation, and evaluate LLM outputs for hallucination and groundedness with domain-specific benchmarks.
  • •Operationalize ML through reproducible workflows, MLOps pipelines, and scalable deployment to cloud-native environments using APIs, Docker, and Kubernetes.

Key Requirements

  • •3-5 years delivering ML projects end-to-end, from data preparation to production deployment.
  • •Proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow.
  • •Experience with modern deep learning architectures including transformers, attention mechanisms, or encoder-decoder models.
  • •Hands-on experience building and optimizing RAG pipelines and evaluating LLM outputs for hallucinations and groundedness.
  • •Solid reinforcement learning knowledge with at least one RL algorithm (e.g., PPO, DQN) and practical experience using OpenAI Gym or equivalent environments.
Experience:3-5 yearsAerospaceAir traffic managementReinforcement learningLLM & RAGMLOps
Education:Bachelor's in Computer Science or Information Technology; Data Science
Skills:Learning agilityFlexibilityPro-activityAgile teamworkUser engagement
Tech Stack:PythonPyTorchTensorFlowScikit-learnTransformersOpenAI GymDQNPPOActor-CriticRAGLangChainLlamaIndexKubeflowAirflowDockerKubernetesMLflowWeights & BiasesApache SparkS3

Company Brief

Thales
Designs and delivers advanced systems and services for aerospace, defence, security, and digital identity and cybersecurity markets, serving government and commercial customers worldwide.
Industry: Defense Technology
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Paris, France
Founded: 2000
WebsiteLinkedIn