Senior Data Scientist at Kifiya Financial Technology

About the Role

• The Senior Data Scientist is a key member of the Data Science department, responsible for developing advanced models, driving innovation in predictive analytics, and delivering insights that shape business strategy.
• This role requires a strong mix of technical expertise, business acumen, and leadership to design and implement high-impact data science solutions in areas such as credit risk, customer analytics, fraud detection, and portfolio optimization.
• The Senior Data Scientist will mentor junior team members, collaborate with cross-functional teams (Data Engineering, Credit Risk, AI & Platform Engineering, and Research & Analytics), and ensure that data science initiatives are production-ready, scalable, and aligned with business objectives.

What You’ll Do

• Design, build, and validate predictive models (classification, regression, clustering, etc.) to support credit risk, customer analytics, and decisioning.
• Partner with Data Engineering to design and refine feature-engineered datasets for scalable model development.
• Work with AI & Platform Engineering to deploy, monitor, and maintain models in production environments.
• Lead deep-dive analyses to identify trends, improve decisioning strategies, and unlock business opportunities.
• Collaborate with the Credit Risk team to ensure models meet regulatory, compliance, and governance standards.
• Guide junior data scientists and analysts, fostering best practices in model development, testing, and documentation.
• Explore new machine learning methods, AI frameworks, and analytical techniques to enhance departmental capabilities.
• Translate complex data-driven insights into clear, actionable recommendations for senior leadership and business stakeholders.

What You’ll Bring

• Master’s or PHD in Data Science, Statistics, Mathematics, Computer Science, or related field.
• 5+ years of experience in data science, with a proven track record of delivering models into production.
• Strong programming skills in Python (preferred) or R, with expertise in libraries such as scikit-learn, TensorFlow, or PyTorch.
• Proficiency in SQL and experience working with large datasets.
• Hands-on experience with model lifecycle management, MLOps, or deployment frameworks.
• Strong background in statistical modeling, machine learning, and data visualization.
• Excellent communication skills, with the ability to present complex concepts to non-technical audiences.
• Experience with Agile delivery and tools such as Jira and Confluence.