Encora Logo

Encora

Data Scientist

Posted Yesterday
Be an Early Applicant
In-Office
Singapore, SGP
Mid level
In-Office
Singapore, SGP
Mid level
Design, develop, deploy, and monitor ML and deep learning solutions including Generative AI and transformer models. Build end-to-end MLOps pipelines, use LLMs, embeddings, vector DBs, and collaborate with data engineering and stakeholders to deliver production AI products and mentor junior staff.
The summary above was generated by AI

 

Data Scientist

Important Information

Location: Singapore

12 months contract

Job Summary

We are seeking a highly skilled and motivated Data Scientist / Senior Data Scientist to join our growing AI and Analytics team. The ideal candidate will have strong expertise in machine learning, deep learning, Generative AI, statistical modeling, and cloud-based MLOps. You will work on designing, developing, deploying, and optimizing AI-driven solutions that solve complex business problems while collaborating with cross-functional teams to deliver high-impact data products.

Key Responsibilities

  • Design, develop, validate, and deploy machine learning and deep learning models for business applications.
  • Build and maintain end-to-end AI/ML pipelines, from data acquisition and feature engineering to model deployment and monitoring.
  • Develop Generative AI applications using Large Language Models (LLMs), embeddings, vector databases, and agentic AI frameworks.
  • Implement AI solutions using frameworks such as LangChain, LangGraph, and other modern AI engineering tools.
  • Apply advanced statistical modeling, optimization techniques, and multi-criteria decision analysis to solve complex business challenges.
  • Develop transformer-based models, reinforcement learning solutions, and other state-of-the-art deep learning architectures where appropriate.
  • Collaborate with data engineering teams to design and optimize ELT pipelines, data transformations, and scalable data architectures.
  • Deploy and manage machine learning models on cloud platforms, preferably AWS, following MLOps best practices.
  • Perform exploratory data analysis, hypothesis testing, feature engineering, and model evaluation.
  • Create clear visualizations, dashboards, and presentations to communicate analytical findings to technical and business stakeholders.
  • Ensure model governance, performance monitoring, and continuous improvement of deployed AI systems.
  • Mentor junior team members and contribute to the adoption of AI and data science best practices.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
  • Minimum 3 years of hands-on experience in Data Science with a reputable organization.
  • Strong analytical and problem-solving skills with experience using structured frameworks such as MECE, Root Cause Analysis, and hypothesis-driven approaches.
  • Proven experience in end-to-end machine learning model development, deployment, and monitoring using MLOps practices.
  • Strong experience with cloud-based ML deployment, preferably on AWS.
  • Deep understanding of machine learning, deep learning, optimization, statistical modeling, and predictive analytics.
  • Hands-on experience with transformer models, reinforcement learning, and modern deep learning architectures.
  • Strong experience in AI Engineering, including:
    • Large Language Models (LLMs)
    • Neural embeddings
    • Retrieval-Augmented Generation (RAG)
    • LangChain
    • LangGraph
    • Vector databases
    • Enterprise Document/Data (EDD) solutions
  • Experience in data engineering concepts including ELT pipelines, structured data transformation, and database technologies.
  • Strong programming skills in:
    • Python
    • R
    • SQL
    • Shell Scripting
  • Experience with Python data science frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and related libraries.
  • Excellent communication, presentation, and data visualization skills.
  • Strong collaboration skills with the ability to work effectively in cross-functional teams.

Preferred Qualifications

  • Experience with CI/CD pipelines for ML applications.
  • Knowledge of containerization technologies such as Docker and Kubernetes.
  • Experience with ML monitoring, model governance, and production model lifecycle management.
  • Familiarity with distributed computing frameworks such as Spark.
  • Experience working in Agile/Scrum environments.
  • Relevant certifications in AWS, Machine Learning, or Data Science are an advantage.

About Encora

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

 

 



Similar Jobs

5 Days Ago
In-Office
Singapore, SGP
Entry level
Entry level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develop machine learning, simulation, and optimization models to analyze manufacturing, equipment, and process data. Build scalable analytics products, dashboards, and automated workflows. Partner with cross-functional engineering teams to improve equipment efficiency, factory productivity, and drive operational excellence through data-driven insights and recommendations.
2 Days Ago
In-Office
Singapore, SGP
Junior
Junior
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Design and deploy computer vision and deep learning models (CNN, LSTM, transformers) for industrial inspection and anomaly detection; extract, clean, and analyze large multimodal datasets; implement MLOps (MLflow, Airflow, Docker) for production deployments; collaborate across engineering, operations, and quality teams; mentor engineers and contribute research outputs and technical documentation.
Top Skills: Apache AirflowAWSC++CnnDashDockerGCPGenerative AiGitHadoopJavaKerasLlmsLstmMlflowOpencvPlotlyPower AutomatePower BIPythonPyTorchRgb-D CamerasSparkSpotfireSQLTensorFlowTransformerYolo
12 Days Ago
In-Office
Singapore, SGP
Junior
Junior
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Design and deploy computer vision and deep learning solutions for manufacturing inspection and monitoring. Extract and clean large datasets, build multimodal AI models, apply MLOps for production deployment, and collaborate with cross-functional teams to translate research into operational systems and documentation.
Top Skills: Apache AirflowAWSC++DashDockerGCPGitHadoopJavaKerasMlflowOpencvPlotlyPower AutomatePower BIPythonPyTorchRgb-D CamerasSparkSpotfireSQLTensorFlowYolo

What you need to know about the Singapore Tech Scene

The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account