Job Overview

  • Date Posted
    January 9, 2024
  • Location
  • Expiration date
    February 3, 2024

Job Description

Moniepoint is a financial technology company digitising Africa’s real economy by building a financial ecosystem for businesses, providing them with all the payment, banking, credit and business management tools they need to succeed.

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 enWork 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.gineers.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.

    About the role

    Location: Remote

    Full time

    What you’ll get to do

  • 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

What we can offer you

  • Culture -We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
  • Learning – We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
  • Compensation – You’ll receive an attractive salary, pension, health insurance,, Employee Stock Options, annual bonus, plus other benefits.

What to expect in the hiring process

  • A preliminary phone call with the recruiter
  • A take-home assessment
  • A technical interview with a Lead in our Engineering Team
  • A behavioural and technical interview with a member of the Executive team.

How to apply: please send us your CV or LinkedIn profile via our career website.

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.