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

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, Num.

Py, 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 Tensor. Flow, Py. Torch, 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