
Data Scientist, CP Axtra
- Bangkok
- Permanent
- Full-time
- Data Analysis: Collect, preprocess, and analyze large datasets to identify trends and actionable insights for retail business challenges.
- Model Development: Design, train, and deploy machine learning models for tasks such as demand forecasting, customer behavior analysis, and inventory optimization.
- Collaboration: Partner with cross-functional teams, including data engineers and business stakeholders, to translate requirements into data-driven solutions.
- Visualization and Communication: Present insights and findings through visualizations and dashboards to inform decision-making.
- Innovation: Stay updated on the latest tools and techniques in data science and retail analytics.
- Feature Engineering:
- Engineer and optimize features to improve machine learning model performance.
- Automate feature extraction pipelines for scalable workflows.
- MLOps:
- Contribute to the deployment, monitoring, and retraining of machine learning models in production environments.
- Data Engineering:
- Assist in designing and maintaining data pipelines and ensuring data quality.
- Education: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Experience: At least 2 years of experience in data science or a related field.
- Technical Skills:
- Proficiency in Python for data analysis and machine learning.
- Strong SQL skills for managing and querying large datasets.
- Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Knowledge of data visualization tools (e.g., Tableau, Power BI, matplotlib).
- Soft Skills: Strong problem-solving, communication, and teamwork abilities.
- Exposure to MLOps tools (e.g., MLflow, Kubeflow, AWS SageMaker).
- Familiarity with data engineering tools (e.g., Apache Spark, Kafka, Airflow).
- Experience in building real-time analytics or personalization systems.
- Clear focus.
- Diverse Workplace (Our members are from around the world!)
- Non-hierarchical and agile environment
- Growth opportunity and career path