Data Scientist (Credit Risk Modeller) (CPT) at Datafin Recruitment

ENVIRONMENT:

• A fast-growing FinTech company seeks the expertise of a Data Scientist – Credit Risk Modeller – with experience in GCP (Google Cloud Platform) and products like LookerStudio, Colab and BigQuery.
• In this role, you will analyse complex data sets, create insightful visualizations, and work closely with stakeholders to develop solutions that support data-driven decision-making.
• You will be responsible for extracting insights, identifying trends, building predictive models and presenting findings to enhance operational efficiency and optimize business processes.
• You will require a Master’s/Bachelor’s Degree in in Mathematics/Statistics/Computer Science or relevant field with proven experience as a Data Scientist or in a similar analytical role & proficiency with tools such as GCP (Google Cloud Platform), Google BigQuery, SQL, Python, and data visualization tools like Google LookerStudio.
• The ideal candidate is analytical, self-driven, adaptable to an unstructured management environment, and passionate about African business, with a sense of adventure and humor.

DUTIES:

Data Collection and Cleaning –

• Collect, extract, and compile data from various sources, ensuring accuracy and completeness.
• Clean, transform, and structure raw datasets for advanced analytics and predictive modeling.
• Identify and resolve data quality issues, inconsistencies, and anomalies.
• Utilize technologies such as SQL, Python, and BigQuery, while staying up-to-date with the latest trends and developments in data analytics.

Data Analysis and Interpretation –

• Perform exploratory data analysis to identify trends, patterns, and relationships within the data.
• Apply statistical techniques, data visualization and predictive modeling to generate actionable insights.
• Translate business problems into rigorous analytical frameworks and model designs.
• Build and maintain multiple predictive models end-to-end, from feature engineering to deployment-ready solutions.
• Implement robust validation frameworks and monitor models for performance, stability, and drift.
• Collaborate with stakeholders to understand business requirements and translate them into analytical approaches.

Reporting and Visualization –

• Create visualizations, dashboards, and reports using Google Looker to effectively communicate data insights to stakeholders.
• Develop and maintain standardized reporting templates and data visualization tools.
• Present findings in a clear and concise manner, tailoring the information to the needs of the audience.

Data-driven Decision Making –

• Collaborate with cross-functional teams to support data-driven decision-making processes.
• Provide analytical support for business initiatives, including market analysis, customer segmentation, and performance tracking.
• Identify opportunities for process improvement, operational efficiency, and revenue optimization through data analysis.

Data Governance and Security –

• Ensure compliance with data governance policies, data protection regulations, and security protocols.
• Adhere to data privacy and confidentiality standards when handling sensitive information.
• Contribute to the development and maintenance of data dictionaries and documentation.

Continuous Learning and Development –

• Stay updated on industry trends, best practices, and emerging technologies in data analysis.
• Expand knowledge of statistical techniques, data modelling, and data visualization tools.
• Participate in training programs, workshops, and professional development opportunities.

REQUIREMENTS:

Qualifications –

• Master’s or Bachelor’s Degree in a relevant field ( Mathematics, Statistics, Computer Science, Data Analytics/Science).

Experience/Skills –

• Proven experience as a Data Scientist or in a similar analytical role, with demonstrated expertise in the credit industry.
• Proficiency in data analysis tools such as GCP (Google Cloud Platform), Google BigQuery, SQL, Python, and data visualization tools like Google LookerStudio.
• Ability to handle and analyse large datasets efficiently.
• Experience with statistical analysis techniques and data modeling.
• Proficiency in Microsoft Excel and other data manipulation tools.
• Familiarity with data governance principles and best practices.
• Knowledge of data privacy regulations and compliance standards is a plus.

ATTRIBUTES:

• Strong analytical and problem-solving skills with keen attention to detail.
• Excellent communication and presentation skills.