Data Scientist Vacancy

  • Full Time
  • Nairobi

Summit Recruitment

Key responsibilities

Development of predictive models (e.g. credit scoring; disbursement; collection rate; retention; repeat rate; customer acquisition; fraud detection; segmentation; social network analysis; etc.)
Development of data processes to mine value from a variety of data sources that include high-volume, transaction-level data.
Provision of analytical and visualization tools and algorithms to various other business teams.
Design and development of algorithms which will constitute components of an intelligent decision platform.
Collaboration with system developers, data engineers, and data architect to implement all of the above.
Develop financial models to cater for Basel III and IFRS9 requirements


Math and Statistics: machine learning; statistical modeling, experiment design, supervised learning (deep learning, decision trees, random forests, SVM, logistic regression, etc.); unsupervised learning (clustering, PCA/PLS, k-means, dimension reduction); reinforcement learning; optimization (gradient descent and variants); Bayesian inference.
Programming and Database: computer science fundamentals, scripting language, e.g. Python; Stats languages and/or packages, e.g., R, SAS, SPSS; databases: SQL and NoSQL; relational algebra; map reduce concepts; Hadoop, Spark, Hive/Pig, Redshift, S3; experience with cloud environments, like AWS or GCP is an advantage.
Communication and Visualization: Ability to relay complex concepts; storytelling skills; translate data-driven insights into decisions an actions; Python and R visualization packages; knowledge of other visualization tools, e.g., Flare, D3.js, Tableau is advantageous.
Domain knowledge and soft skills: Passionate about the business; curious about data; influence without authority; hacker mindset; problem solver; strategic, proactive, creative, innovative and collaborative.

Key requirements

A postgraduate degree, Honours, Masters or Phd degree in Computer Science, Mathematics, Physics, Statistics, Engineering, or similar.
A mixture of multidisciplinary skills ranging from an intersection of computer science, mathematics, statistics, communication and business.
Experience with machine learning and implementation of solutions to drive decision processes.
Strong mathematical aptitude and problem solving ability.
Ability to work independently, but also a strong team ethic.
Excellent oral and written communication skills.
Proven ability to complete projects timeously and in line with requirements.

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