Click here to apply



L-IFT (Low Income Financial Transformation) is a Netherland based Research Company that specializes in diaries research. L-IFT uses a unique technology-led diaries research methodology to bring data empowerment to low-income communities which facilitates evidence-based policy design and service delivery. L-IFT conducts research projects in various countries. Our largest current project is Small Firm Diaries in seven countries, together with New York University – Financial Access Initiative. L-IFT is also building data with refugees, youth, women micro-entrepreneurs, small holder farmers and corner shops. The company is increasingly focusing on self-reported data and empowering people to use their own data for their development as entrepreneurs or employees. It had developed an app named Finbit that is expected to be used by thousands of youth, women, refugees and other insufficiently understood groups.

L-IFT is an organization for talented people with different backgrounds and perspectives. We thrive on our diversity and the team is composed of experts around the world. L-IFT offers sound employment conditions including working from home with opportunities of personal growth and development. For more information, please visit

If you are interested to work in this dynamic organization, L-IFT is looking to hire a data expert that is based in Nairobi who will work intensively with our current lead data expert, who reports directly to the Managing Director.


Job Summary

L-IFT holds a wealth of high-quality time-series data since 2014 from diaries studies from more than ten countries. This position will play a lead role in further analyzing the data as well as building the system and processes to structurally deliver the required findings. The post requires superior analytical thinking, and ability to apply technical and statistical knowledge to analyze data, and to provide the findings that clients and users need. These include but not limited to data sampling, data analysis, and summaries, presentation of data findings in reports and workshops, etc. The role is responsible for providing guidance and technical solutions around issues of data collection, preparation, analysis and interpretation of data. The data expert must be an advanced ‘R’ user.

Ideally the data expert has a strong statistical background and has the abilities to design a sample and provide various statistical analyses.


Required Qualifications and Experience

  • Have completed a Bachelor’s degree in a quantitative field such as statistics, mathematics, computer science, data science, or similar fields.
  • Masters is preferred
  • Experience in managing and manipulating large, complex datasets, ideally some time series experience
  • Experience in working with data management and analysis package, specifically in “R”- Phyton is an added advantage
  • Experience in using advanced Excel features to conduct data analysis such as pivot tables, Vlookup, and if-else statements
  • Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise
  • Strong problem solving and resolution skills.
  • Excellent verbal and written communication skills in English required due to the nature and level of interaction with other teams and senior management.
  • Demonstrated ability to prioritize workload and manage multiple projects while meeting deadlines.
  • Able to work independently and happy to work at distance with colleagues from around the world, but without office and infrequent face-to-face interaction


How to apply

Candidates with the required profile and proven experiences, and a strong desire to work for L-IFT, are invited to complete the Job Application form on our website: (open-vacancies) (strictly required to use the application form for providing details, writing their motivation text and uploading their CV). Deadline for application is on 27th June 2021. Applications will be reviewed on a rolling basis.


Click here to apply