Senior Data Scientist (Consumer Experience)

Grab; Singapore; Presencial; SGD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Gym membership

Descripción de la vacante

Grab is seeking a data science/ML specialist to enhance user personalization through ranking, translations, and agentic content. You will work with product, marketing, and engineering to deploy ML/LLM solutions, build data pipelines, and ensure observability across production systems.

You will guide end-to-end ML lifecycle activities, including feature selection, tuning, and model validation, leveraging Scikit-Learn, Pandas, XGBoost, TensorFlow, and PyTorch.

Formación

• 4+ years in data science or ML with a relevant Master’s degree.
• Proficient in Python, R or Java plus pipeline and ETL experience.
• Apply predictive modeling algorithms understanding production trade-offs for deployment.
• Use ML frameworks such as Scikit-Learn, Pandas, XGBoost, TensorFlow, or PyTorch.
• Manage end-to-end ML lifecycle including feature selection, tuning, and validation.

Responsabilidades

• Enhance targeting with relevance ranking, translation models, and agentic content.
• Analyze data to understand user behavior for personalization.
• Collaborate with product, marketing, and engineering on ML and LLM deployment.
• Build models, data pipelines, observability, and evaluation frameworks for production systems.
• Use GenAI and AI coding assistants to accelerate development and evaluation workflows.

Conocimientos

Python

R

Java

ETL

Data pipelines

Scikit-Learn

Pandas

XGBoost

TensorFlow

PyTorch

ML lifecycle

Observability

GenAI

Educación

Master's degree

Herramientas

TensorFlow

PyTorch

XGBoost

Pandas

Descripción del empleo

What you'd do:

• Enhance communication targeting with relevance ranking, translation models, and agentic content.
• Analyze quantitative and qualitative data to understand user behavior for personalization.
• Collaborate with product, marketing, and engineering on ML and LLM deployment.
• Build models, data pipelines, observability, and evaluation frameworks for production systems.
• Use GenAI and AI coding assistants to accelerate development and evaluation workflows.

What they want:

• Hold at least four years in data science or ML with a relevant Master's degree.
• Demonstrate proficiency in Python, R, or Java plus pipeline and ETL experience.
• Apply predictive modeling algorithms understanding production trade-offs for deployment.
• Use ML frameworks such as Scikit-Learn, Pandas, XGBoost, TensorFlow, or PyTorch.
• Manage end-to-end ML lifecycle including feature selection, tuning, and validation.
• Engage AI tools and emerging technologies to enhance productivity and workflows.

Hold at least four years in data science or ML with a relevant Master's degree.

Demonstrate proficiency in Python, R, or Java plus pipeline and ETL experience.

Apply predictive modeling algorithms understanding production trade-offs for deployment.

Use ML frameworks such as Scikit-Learn, Pandas, XGBoost, TensorFlow, or PyTorch.

Manage end-to-end ML lifecycle including feature selection, tuning, and validation.

Engage AI tools and emerging technologies to enhance productivity and workflows.