Job description

Due to an internal promotion, M-KOPA is looking to welcome an additional Senior Data Scientist to their distributed Data Science and Analytics team. As a senior member of the team, you will provide critical data insights and predictions that drive the business as well as contributing the teams standards and vision. Our vision is to be the smartest company in Africa and you will play a crucial part in that.  

With over a million customers across multiple geographies, the value derived from our data is essential to both everyday operations and critical business decisions. Data Science at M-KOPA covers a wide range of activities, from building predictive and explanatory models and communicating complex insights, to running experimental pilots and evaluating casual inference. In this position, you’ll sit inside a small team that thinks creatively, builds robustly and communicates clearly. The ideal candidate will have a strong background in building end-to-end data products; including collaborating with stakeholders to scope requirements, extracting and transforming data, building and evaluating models/analyses and deploying these in repeatable and robust manner. Given that a large part of our data and business operations is centered around finance and credit, candidates with strong economics or finance backgrounds are encouraged to apply. 

SPECIFIC RESPONSIBILITIES

Ultimately the responsibility of the Senior Data Scientist is to be a key contributor to the wider data team and generate data driven insights that directly drive and improve the business.

Below are some examples of how this can be achieved:

•  Develop a deep understanding of the business context and our data which contributes and translate to impactful, relevant outputs.
•  Design models and analysis alongside associated business implementation in partnership with key stakeholders.
•  Develop predictive models and analyses with a strong focus on reproducibility, accuracy and evaluation.
• Communicate analysis and drive improved decision making with the broader business in a straight-forward, clear manner
•  Contribute to company-spanning frameworks and tools for measuring business, credit and sales performance and evaluating business changes and pilots
• Collaborate with senior business stakeholders on analytic methods, data-driven decision making
• Provide support and mentorship to junior team members.

EXPERIENCE AND SKILLS

Education: A degree in computer science, mathematics or related quantitative field / demonstrated self-directed learning.

Experience: 4+ years in a role with a similar focus, 2+ years of predictive modelling experience preferred.

Knowledge / Skills:

Required

• Advanced experience building predictive and explanatory models that solve specific business problems.
•  Advanced skills in Python or R, ideally Python.
• Strong ability to communicate technical details visually and in written form to broader stakeholders.
• Strong attention to detail and investigative nature to ensure error-free, high quality, reproducible analysis.
• Experience working with automated systems to produce model outcomes with ongoing monitoring.
• Experience with collaborative data and software development via git and you’re comfortable in the command line.
• Enjoy abstracting, generalizing and create efficient, scalable processes that benefit the wider team.

Additional assets

•  Experience with one or more of the following types of modelling approaches: credit scoring models, cost sensitive learning, ARIME and LSTM forecasting.
• Experience with running operational experiments and evaluating casual inference.
• Experience with Microsoft Azure, similar cloud providers and tools also a plus
• Familiarity with agile data ops development processes, unit testing, source control, continuous integration, etc.
• Experience with data visualization tools for stakeholder communication.

COMPENSATION:

 Competitive package covering a monthly salary reflective of the candidate’s experience and skills, performance bonus and medical benefits.

TO APPLY: Please submit your CV and cover letter telling us why you would like to be considered for this role.