As a Data Scientist, you will lead the development of advanced analytics and machine learning solutions within banking and payments environments. You will transform complex data into predictive models and actionable insights, enabling strategic decision-making through close collaboration with business and technical stakeholders.
What You’ll Do and How You’ll Succeed
- Lead the design, development, and deployment of machine learning models and statistical analyses to solve complex business problems in banking and payments domains
- Analyse large and complex datasets using tools such as SAS, Hadoop, R, SQL, Python, and Hive, ensuring data integrity and optimised analytical processes
- Apply advanced statistical and machine learning techniques including Neural Networks, Gradient Boosting, Linear and Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, and Factor Analysis to generate actionable insights
- Develop predictive models, run experiments, and validate outcomes to support business strategies and operational improvements
- Collaborate with cross-functional teams to communicate insights clearly through data visualisation and structured recommendations using Excel and PowerPoint
- Lead data storyboarding and presentation efforts, translating complex technical findings into clear, persuasive narratives for both technical and non-technical stakeholders
We’d Love to Hear From You If…
Experience
- You have 5+ years of hands-on experience in data science, analytics, or a related field within banking, payments, or similar industries
- You have proven experience working in fast-paced environments and managing multiple projects simultaneously
Technical Expertise
- You have strong experience with data analysis and programming tools including SAS, Hadoop, R, SQL, Python, and Hive
- You have deep proficiency in statistical modelling and machine learning techniques such as Neural Networks, Gradient Boosting, Linear and Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, and Factor Analysis
- You are skilled in creating data visualisations, presentations, and data storytelling using tools such as Excel and PowerPoint
Ways of Working
- You demonstrate strong problem-solving and analytical thinking, translating complex data into actionable insights
- You communicate effectively with both technical and non-technical stakeholders, ensuring clarity and impact in your recommendations mentation and presentations on-making