CPO Pte. Ltd. – Data Scientist

As a Data Scientist, you will be at the forefront of our data analytics efforts, working closely with cross-functional teams to develop and deploy advanced analytical solutions. You will be responsible for analyzing large datasets, building predictive models, and generating actionable insights to inform business decisions. The ideal candidate will possess strong analytical skills, a deep understanding of statistical methods and machine learning techniques, and a passion for solving complex problems using data.

Key Responsibilities:

1. Collaborate with stakeholders to understand business objectives and identify opportunities for leveraging data analytics to drive business value.
2. Collect, clean, and preprocess large datasets from multiple sources to ensure data quality and integrity.
3. Apply statistical analysis and machine learning techniques to develop predictive models and algorithms for solving business problems.
4. Evaluate model performance and iteratively refine models to improve accuracy and effectiveness.
5. Generate actionable insights and recommendations based on data analysis, and present findings to stakeholders in a clear and compelling manner.
6. Work closely with engineering teams to deploy and operationalize analytical models in production environments.
7. Stay abreast of the latest developments in data science and machine learning, and proactively explore new techniques and methodologies to enhance analytical capabilities.
8. Collaborate with cross-functional teams to integrate data analytics into business processes and decision-making workflows.
9. Adhere to best practices in data governance, security, and compliance, ensuring the ethical and responsible use of data throughout the organization.

Qualifications:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field
• Experience with developing and deploying predictive models and algorithms would be a plus
• Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy) would also be a plus
• Strong understanding of statistical methods and machine learning techniques, including linear regression, logistic regression, decision trees, random forests, and neural networks.
• Experience working with big data technologies (e.g., Hadoop, Spark) and distributed computing frameworks.
• Solid understanding of data visualization techniques and tools (e.g., Matplotlib, Seaborn, Tableau).
• Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced, dynamic environment.
• Strong communication and presentation skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.
• Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.