Moniepoint Inc. is a leading financial technology company that provides a seamless platform for businesses to accept digital payments, access credit and access simple business management tools that enable them to grow with ease. We are the parent company of TeamApt Ltd and Moniepoint MFB and we support over 600,000 businesses to process $12 billion monthly through our digital payment acceptance channels.
What we do
Engineering at Moniepoint is an inspired, customer-focused community, dedicated to crafting solutions that redefine our industry. Our infrastructure runs on some of the cool tools that excite infrastructure engineers.
We also make business decisions based on the large stream of data we receive daily, so we work daily with big data, perform data analytics and build models to make sense of the noise and give our customers the best experience.
If this excites you, it excites us too and we would love to have you.
What you’ll get to do
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Develop company A/B testing framework and test model quality.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
To succeed in this role, we think you should have
- Strong problem solving skills with an emphasis on product development.
- Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- 4-7 years of relevant work experience
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
- We’re looking for someone with a minimum of 3 years of experience manipulating data sets and building statistical models.
- BSc in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools: C, C++, Java.
Some of the technologies you’ll get to work with
- Java (latest versions)
- C++, C
- SQL, Python, R
Method of Application
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