Thales

2 weeks ago

Data Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

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

Website LinkedIn

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Thales

2 weeks ago

Data Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

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

Website LinkedIn