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
Responsibilities
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 AND SKILLS
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
stakeholders
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
production
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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