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Data Analyst Intern

Singapore, North East, SingaporeData

Job description

Who are we?

With a vision of making an impact on Asia’s healthcare landscape and an aim to push healthcare beyond current times, Speedoc is passionate about making healthcare more convenient, accessible, and affordable to all. This is done by providing a full suite of tech-enabled healthcare services on demand including doctors, nurses, allied care professionals, ambulances, and medication delivery across Singapore and Malaysia.

Speedoc is an innovative healthcare start-up that is entrusted by brands and agencies including the Ministry of Health, and Temasek Holdings as a partner to deliver projects in public health. Speedoc positions itself at the forefront as the market leader in the digital healthcare landscape and the team constantly identifies opportunities for growth, improvement, and game-changing initiatives that can be implemented in our ever-expanding product roadmap.

With 3 engines of growth across B2G, B2B, and B2C, we are seeking a highly independent talent to join our team.

The ML & Data Analyst Intern supports the data analysis and decision-making processes within an organization with the use of machine learning. The specific responsibilities include :-

1. Data Engineering:

  • Building data pipelines to collect raw data from various sources such as databases, spreadsheets, and APIs.
  • Cleaning and preprocessing data to ensure accuracy and completeness.

2. Data Analysis:

  • Performing exploratory data analysis (EDA) to identify trends, patterns, and outliers.
  • Utilizing statistical methods to analyze and interpret data.
  • Creating visualizations (charts, graphs, dashboards) to communicate findings effectively.

3. Machine Learning:

  • Support the development and implementation of machine learning algorithms and models.
  • Collaborate with the team to refine existing ML models and experiment with new approaches.
  • Contribute ideas and insights to improve data quality, model performance, and processes.

4. Report Generation:

  • Generating regular reports summarizing key performance indicators (KPIs) and insights. 
  • Presenting findings to team members or management through written reports or presentations.

4. Database Management:

  • Assisting in the development and maintenance of databases.
  • Writing SQL queries to extract and manipulate data.

5. Tool Proficiency:

  • Using data analysis tools such as Excel, Python, R, or other specialized tools.
  • Familiarity with data visualization tools like Tableau or Power BI.

6. Collaboration:

  • Collaborating with cross-functional teams, including business analysts, engineers, and decision-makers.
  • Participating in team meetings and contributing insights to solve business problems.

7. Problem Solving:

  • Identifying and resolving data-related issues or discrepancies.
  • Proposing solutions for improving data quality and analysis processes.

8. Learning and Development:

  • Staying updated on industry trends, data analysis techniques, and tools.
  • Actively seeking opportunities to expand skills and knowledge in data analytics.

9. Documentation:

  • Documenting data analysis processes and methodologies.
  • Creating and maintaining documentation for datasets and analysis results.

10. Quality Assurance: - Ensuring the accuracy and reliability of analytical results. - Conducting validation checks to verify the integrity of data.

11. Ad-hoc Analysis: - Conducting ad-hoc analyses based on the specific needs of the team or organization.

Job requirements


  • Pursuing a degree in a relevant field (such as Data Science, Statistics, Computer Science, or a related discipline).
  • Strong analytical and problem-solving skills.
  • Proficiency in programming languages like Python or R.
  • Familiarity with databases and SQL.
  • Excellent communication and presentation skills.
  • Attention to detail and the ability to work independently or as part of a team.