Data Scientist – Level 1 (STEM Graduate / Junior)

We are seeking a highly motivated and academically strong Data Scientist – Level 1 to join a team of talented data professionals solving complex business challenges through data, analytics, and machine learning. This opportunity is ideal for recent graduates or early-career professionals who have a strong foundation in mathematics, statistics, computer science, engineering, or a related STEM field and are eager to apply their knowledge to real-world problems. We are specifically looking for high-performing graduates who have achieved excellent academic results from reputable universities and institutions.

What You'll Do As a Data Scientist – Level 1, you will work alongside experienced data scientists and engineers while developing your technical and problem-solving capabilities. Your responsibilities will include: 
 
 • Performing exploratory data analysis (EDA) to identify patterns, trends, and insights 
 • Assisting in the design, development, and evaluation of machine learning models 
 • Cleaning, preparing, and transforming data for analysis and modelling 
 • Developing analytical solutions to solve business problems 
 • Writing clean, maintainable, and well-documented Python code 
 • Conducting statistical analysis and interpreting results 
 • Presenting findings and recommendations clearly to technical and non-technical stakeholders 
 • Collaborating with cross-functional teams on data-driven initiatives 
 • Continuously learning and applying new techniques, tools, and methodologies 


Requirements 
 
 • Bachelor's Degree (BSc, BEng, BCom Honours, BSc Honours, MSc or equivalent) in: Data Science, Computer Science, Statistics, Mathematics, Engineering, Actuarial Science, Physics Or another quantitative STEM discipline 
 • Excellent academic record throughout university studies 
 • Degree obtained from a recognised and reputable university or higher education institution 
 • Strong results in mathematics, statistics, machine learning, programming, or related quantitative subjects 
 • Solid understanding of data science and machine learning fundamentals 
 • Proficiency in Python 
 • Experience with libraries such as: Pandas, NumPy, Scikit-learn 
 Advantageous Skills 
 
 • Exposure to machine learning projects through academic work, internships, personal projects, or competitions 
 • Experience with SQL and relational databases 
 • Familiarity with cloud platforms such as AWS, Azure, or GCP 
 • Exposure to TensorFlow, PyTorch, or other machine learning frameworks 
 • Knowledge of data visualisation tools such as Power BI, Tableau, or similar 
 • Participation in Kaggle competitions, research projects, or published academic work