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.
Your Opportunity and Mission
We are looking for talented and passionate Data Scientist to join the Growth team. Data science and optimization are key drivers for Moniepoint’s business growth and the Data Scientist joining will have the opportunity to build and own the most important models including our attribution and marketing mix models
- Develop, test and productionize attribution and predictive algorithms by using state of the art machine learning algorithms and optimisation models
- Contribute to one or more of the following areas: attribution modeling, CAC/mCAC modeling, LTV prediction, marketing mix modeling and multichannel attribution and testing
- Design experiments and interpret the results to draw detailed and actionable conclusions
- Work in cross-functional teams across disciplines such as product, engineering and business.
- Develop, test and own our production marketing attribution models for better budgeting and increased marketing efficiency
You Have
- 5 years of professional experience outside of an academic and internship setting, in a quantitative analysis role in top companies. FMCG or Fintech preferred.
- Holds at least an MSc, and preferably a PhD in a scientific discipline such as Physics, Statistics, Engineering, Computer Science or Mathematics
- Deep theoretical and applied knowledge in the following areas: statistical inference, bayesian statistics, causal inference, time series analysis and mathematical optimisation.
- Extensive experience at least in Multichannel Attribution Modeling and Marketing Mix Modeling
- Extensive experience in statistical programming (Python) and experience working with popular tools such as Pandas, SciPy, XGBoost, Jupyter/iPython notebooks and well-known modeling packages such as PyMC3
- Extensive experience with the end-to-end predictive/prescriptive model development cycle, from problem definition to productionalization and maintenance. This includes excellent data modeling and SQL skills, and familiarity with Cloud infrastructure.
- Demonstrated experience in designing and analyzing experiments in digital products (A/B test, multivariate, etc.)
- Experience with the application of statistical modeling and advanced analytics to provide product-shaping insights
- Excellent spoken and written English
Method of Application
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