Welcome to Credable!
We build embedded finance solutions that provide access to finance to people and places that previously were left in the dark.
Picture not being able to store your earnings securely, transmit or receive money over great distances, acquire credit, or participate in the digital economy. This isn’t a trivial inconvenience, it affects the livelihoods, education, health, and opportunity of those considered “unbanked”.
On the flip side
There are businesses (e.g. mobile network operators, e-commerce platforms, and service providers) who have captive customers in their channels and rich data but lack the capabilities to offer those customers reliable access to financial services.
Financial service providers (banks & insurance companies) that possess the capital and licenses, but cannot reach the customers with no physical access to them; therefore unable to expand their digital portfolio and solve the issue of financial independence across the continent...
The Role:
We are looking for a Senior Data Scientist to join our Data Team as we continue to build out our Credit Scoring Capabilities and Data Analytics functions. Reporting to the Head of Data, you will be a highly analytical and detail-oriented professional passionate about developing and maintaining credit risk models.
You will play a pivotal role in designing and maintaining scalable data pipelines and will contribute significantly to our data initiatives. Responsibilities will include leading the development and maintenance of credit risk models, overseeing predictive analytics projects, and conducting advanced data analysis to uncover insights that drive our business forward.
Key Responsibilities:
- Collaborate with 3rd party partners on credit scoring, modeling, and evaluation of our lending product portfolio
- Develop credit risk models using advanced statistical and machine learning techniques
- Analyze credit data to identify patterns and trends that inform our credit decision-making processes
- Work closely with data engineering and software engineering teams to ensure efficient data collection, processing, and storage
- Develop predictive models for credit risk assessment, fraud detection, and other business use cases
- Monitor and analyze the performance of credit risk models and recommend improvements
- Create and maintain data dashboards and reports to communicate insights to stakeholders
- Stay current with new technologies and trends in data science and credit scoring
- Mentor junior data scientists within the team
- Support the Head of Data in driving the data strategy aligned with business goals
The finer points: What we are looking for from you
- Master's degree in Computer Science, Statistics, Mathematics, or a related field
- Minimum of 5 years of experience in data science or a related field
- In-depth knowledge of credit risk models, regulations, and industry best practices
- Strong proficiency in programming languages such as Python or R
- Expertise in statistical and machine learning techniques, including logistic regression, decision trees, random forests, gradient boosting machines, neural networks, etc.
- Strong analytical and problem-solving skills
- Ability to translate business objectives into data-driven solutions
- Excellent communication skills, capable of presenting complex data insights to non-technical stakeholders
- Ability to manage multiple projects simultaneously
- Proven ability to work effectively with third parties and cross-functional teams
- High level of initiative and a proactive approach to problem-solving
- Practical, hardworking, hands-on, results-oriented professional with the ability to achieve high-quality results
Our team’s values: what we live by
- Integrity: Be consistent in your actions, delivering on promises with transparency.
- Respect: Ensure that we cultivate a feeling of being valued, allowing people to lead.
- Accountability: OWN IT! Our actions dictate our performance.
- Openness: With diversity in our ideas, our team are free to share their views and opinions.
- Continuous Improvement: Learn from mistakes, change for the better, and grow as a team.
- Data-Driven in Our Decisions: Let's make decisions on facts not assumptions, it’s a no-brainer, in data we trust!
We believe in equal opportunities, we welcome applications from diverse backgrounds. However experience working in FinTech, Banking/Finance, or Telcos is a big plus.
