Graduate Data Scientist

Key Duties and Responsibilities Data Exploration & Preparation Collect, clean, and transform large datasets from various sources. Work with both structured and unstructured data to ensure quality, consistency, and usability. Support the development and maintenance of data pipelines and analytical datasets. Machine Learning & Analytics Assist in building and testing machine learning models. Contribute to feature engineering and model improvement initiatives. Support the implementation of anomaly detection and predictive analytics solutions. Evaluate model performance and document key findings. Reporting & Visualisation Create interactive dashboards and reports using Power BI. Translate complex analyses into clear, actionable business insights. Present findings to both technical and non-technical stakeholders. Collaboration & Innovation Partner with analysts, engineers, and business teams to understand data requirements. Contribute to automation and process improvement projects. Help develop solutions that improve operational efficiency and decision-making. Continuous Learning Stay up to date with emerging tools, technologies, and industry trends. Continuously explore new approaches to analytics and machine learning. Essential Skills, Qualifications & Experience Qualifications Bachelor's degree in: Data Science, Statistics, Computer Science, Mathematics, Economics, Finance or a related quantitative field. Recent graduates and candidates with up to 2 years' experience are encouraged to apply. Technical Skills Working knowledge of Python (Pandas, Scikit-learn, Matplotlib or similar libraries). Familiarity with SQL and basic database concepts. Experience with Power BI, Excel, or other reporting tools. Understanding data analysis and machine learning fundamentals. Advantageous Experience Exposure to Git or version control tools. Knowledge of cloud platforms and data engineering concepts. Experience with financial or transactional data. Why Join Us? Work on real business problems using modern data science techniques. Gain exposure to machine learning, financial analytics, business intelligence, and automation. Collaborate with experienced professionals in a supportive learning environment. Accelerate your professional growth through practical, hands-on experience. Build a strong foundation for a long-term career in data science and analytics. If you are eager to learn, thrive on problem-solving, and want to apply your technical skills in a fast‑paced professional environment, we would love to hear from you. #J-18808-Ljbffr