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Head Of Data Science

Nairobi, Kenya

Salary rangeConfidential | Contract type: Permanent

You have 10 days left to apply for this job.

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Job Summary

The Head of Data Science will be a senior member in the M-KOPA Strategy and Data team and will drive M-KOPA’s data vision of being the smartest and most effective company in Africa. They will report directly into the Chief Strategy and Data Officer. The role will oversee all of M-KOPA’s data science and analytical engineering teams and depending on skills and experience, could also grow to oversee other data functions including business intelligence and data operations.
LOCATION: Kenya, UK and/or remotely


  • Lead and manage the data science and analytical engineering sections of the Strategy and Data team
  • Help develop and steer the company’s overall data vision and strategy
  • Drive data-driven decision making through the development of insights and efficiencies across the company
  • Proactively identify the most important questions the business should be answering using data science and advanced analytics and then design and test data-driven hypotheses and then manage the team to test and execute against those
  • In collaboration with our software development team, lead to the development of our data / analytical engineering pipelines; aggregating event-streams into question focused data sets
  • Own the decisions and implementation of our data architecture and tool/stack selection
  • Support the team in the building and operationalizing of machine learning models and in some circumstances, building some models yourself.
  • Provide support and mentorship to all members of the team to develop their skills and capabilities
Experience: 4+ data experience, 2+ years of management experience
Knowledge / Skills: Required
  • Experience managing data science/data engineering teams
  • Advanced skills in Python or R, ideally both.
  • Strong experience with SQL and SQL-inspired declarative query languages
  • Ability to think creatively about business and engineering problems and understand how to apply data science processes to create measurable results
  • Ability to communicate technical details visually and in written form to broader
  • Meticulousness in ensuring error-free, high-quality, reproducible analyses
  • Experience with collaborative data and software development via git Additional assets
  • Experience building predictive and explanatory models and putting them into
  • Experience with pythandas, airflow
  • Experience with dbt (and Jinja) or a similar tool
  • Experience with using automated deployment pipelines
  • Experience with distributed computing tools such as Spark
  • Experience with Microsoft Azure (Synapse Analytics, Data Factory, Data Lake,
  • U-SQL), or other similar cloud providers and tools
  • Familiarity with agile data ops development processes, unit testing, source control, continuous integration, etc. and their application to data workflows
  • Experience with data visualisation tools (such as Power BI or Tableau, GGPlot2, D3.js, Seaborn, Matplotlib, Dash etc.)
  • Experience with modern machine learning methods for signal processing / time-series analysis (e.g. HMMs, Kalman Filters, LSTM Neural Nets, etc.).
  • Experience with advanced experiment design and causal methods for time series (e.g. casual inference based on BSTS, experiment design using multi armed bandits etc).

Job Requirements

Required education: Bachelor's degree
Required relevant work experience: 7 years
Required languages: English (Spoken: fluent | Written: fluent)

Mandatory attachments

Please have a scan or photo of these documents ready when you start the application:

Self-prepared CV file - the employer wants to see a CV that you have prepared yourself
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