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- Support Data Science Projects: Assist in the end-to-end lifecycle of data science projects, including data collection, preprocessing, and analysis, while learning to apply machine learning techniques.
- Model Development: Collaborate with senior team members to design and implement machine learning models that address business challenges, gaining exposure to advanced algorithms and methodologies.
- Data Analysis: Conduct exploratory data analysis (EDA) to identify trends, patterns, and insights from data, contributing to the strategic initiatives of the company.
- Collaboration: Work closely with cross-functional teams, including data engineers and product managers, to ensure alignment on project goals and deliverables.
- Documentation and Reporting: Help document processes and findings, creating clear reports and visualisations that communicate results to technical and non-technical stakeholders.
- Continuous Learning: Stay informed about industry trends and new technologies in data science and machine learning, actively seeking opportunities to expand your skill set.
- Education: A degree in a relevant field such as Computer Science, Statistics, Mathematics, or Data Science is preferred.
- Experience: 0-2 years of relevant hands-on experience in data science or related fields, including internships or co-op placements that involved practical application of data analysis and machine learning techniques.
- Technical Skills: Proficiency in programming languages such as Python or R. Familiarity with machine learning libraries (e.g., scikit-learn) and data manipulation tools (e.g., Pandas) is a plus.
- Data Management: Understanding of SQL and experience with data analysis and visualisation tools (e.g., Tableau, Matplotlib).
- Analytical Skills: Strong problem-solving abilities and a passion for data analysis and insights.
- Soft Skills: Effective communication skills, a willingness to learn, and the ability to work collaboratively within a team.
