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Job Description
The successful candidate will work with A/P Dr Sergio Hernandez Marin in the Data Analytics Consulting Center on both internal-facing (NUS) and external facing (startups, SMEs, MNC) Data Science and Data Architecture roles.
The main responsibilities of the position include:
1. Data Analysis and Modeling:
- Utilize advanced statistical and machine learning techniques to analyze complex datasets.
- Develop predictive models and algorithms to extract meaningful insights and patterns.
2. Data Architecture and Management:
- Design and implement robust data architectures to support the project's data needs.
- Work on data integration, ensuring seamless flow and accessibility of data across different components of the project.
3. Collaboration with Interdisciplinary Teams:
- Engage with a diverse team of stakeholders, to integrate data science solutions into the broader project framework.
- Communicate findings effectively to non-technical stakeholders.
4. Teaching Short Courses on Data Science:
- Design and deliver short courses on data science topics to internal team members or external stakeholders.
- Provide training sessions on the application of data science methodologies and tools.
5. Experimental Design and Hypothesis Testing:
- Contribute to the formulation of research hypotheses and experimental design.
- Implement and conduct experiments, ensuring the rigor and reproducibility of the research process.
6. Software Development and Implementation:
- Develop custom tools and software solutions to facilitate data analysis and visualization.
- Ensure the scalability and efficiency of software components in handling large datasets.
7. Documentation and Reporting:
- Maintain comprehensive documentation of methodologies, data sources, and analysis processes.
- Prepare regular progress reports and contribute to academic publications.
8. Stay Current with Emerging Technologies:
- Keep abreast of the latest advancements in data science, machine learning, and relevant technologies.
- Integrate innovative approaches and tools to enhance the project's methodologies.
Qualifications
• Qualifications / Discipline:
Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field, with a specialization in Data Engineering and Data Architecture.
• Skills:
1. Data Science and Statistics Proficiency:
- Demonstrated expertise in data science methodologies and statistical analysis.
2. Programming Skills:
- Proficiency in programming languages such as Python, SQL, and Javascript.
3. Data Engineering and Data Architecture:
- Strong background and practical experience in Data Engineering and Data Architecture, encompassing the design and implementation of robust data structures.
4. Data Visualization:
- Proven experience using data visualization tools to present complex data in a comprehensible manner.
5. Database Management Systems:
- Hands-on experience with various database management systems, ensuring efficient data storage and retrieval.
6. Cloud Platforms:
- Familiarity with cloud platforms and the ability to leverage cloud-based solutions for data analysis and storage.
7. Communication and Collaboration:
- Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders.
- Proven ability to collaborate effectively within a diverse team.
• Experience:
At least 3-5 years of experience in Data Science / Data Engineering
