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Senior Data Scientist, MNO Data

GiveDirectly, Inc Kisumu Full Time Posted 2026-11-02
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GiveDirectly is hiring a Senior Data Scientist to improve and extend analytical method templates for inferring residence location from Mobile Network Operator data. The role involves adapting methods for each operator, writing specifications for data engineers, and running workshops, with substantial international travel (25-50% of time).

  • Senior-level data science role focused on location inference from MNO data
  • Remote work with 25-50% international travel
  • Hiring prioritized in Kenya among other countries
Source BrighterMonday Kenya Salary Not enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.

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CountyKisumuCityKisumuContractFull TimePosted2026-11-02Close dateNot specifiedExperienceNot specifiedSourceBrighterMonday Kenya
senior data scientistdata scienceMNO datalocation inferenceKisumuremotefull timeinternational travelGiveDirectlymachine learningsecurityinternship

AI summary

GiveDirectly is hiring a Senior Data Scientist to improve and extend analytical method templates for inferring residence location from Mobile Network Operator data. The role involves adapting methods for each operator, writing specifications for data engineers, and running workshops, with substantial international travel (25-50% of time).

  • Senior-level data science role focused on location inference from MNO data
  • Remote work with 25-50% international travel
  • Hiring prioritized in Kenya among other countries
  • Involves technical leadership and cross-team collaboration
  • Full-time position with standard 8 to 5 working hours
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AI salary guide

Not enough public data

Not enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.

Can you qualify for this role?

  • UnclearRelated work experienceThe text mentions experience, but the exact level should be confirmed at source.
  • PreferredPractical evidence in security, internship, part_timeThe tags and summary point to skills connected with this role.
  • RequiredAvailability to work in KisumuThe vacancy is associated with this location.
  • UnclearComfort with the Full Time contract termsConfirm hours, duration, probation and benefits at the original source.

Documents to prepare

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  • Role specificCover letter or short employer message
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Application tips for this job

  • Place your strongest Senior Data Scientist, MNO Data evidence in the first half of your CV.
  • In your cover letter or employer message, connect your experience to GiveDirectly, Inc and the role in Kisumu.
  • Add concrete examples related to security, internship, part_time, ideally with measurable outcomes or clear responsibilities.
  • Follow the instructions from BrighterMonday Kenya; avoid sending documents to unofficial contacts or copied links.
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Interview preparation

  • What experience makes you a strong fit for this Senior Data Scientist, MNO Data role in security, internship?
  • How have you handled responsibilities similar to those in this job post?
  • Are you available to work in Kisumu under the listed contract or schedule?
  • Prepare examples with clear responsibilities, tools used and measurable outcomes.
  • Review the source and research GiveDirectly, Inc before the interview.

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Original source description

G

Senior Data Scientist, MNO Data

GiveDirectly, Inc

Software & Data

Today

New

Kisumu

Full Time

Confidential

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Language Requirement:

English

Work Type:

Full Time

Working Hours:

8 to 5

Applicant Location:

Kenya

Job descriptions & requirements

About GiveDirectly

GiveDirectly has delivered more than $1B in cash directly to 2+ million people living in poverty and crisis across 15 countries. We’re growing fast and expect to hit $1B in revenue in 2026 with significant growth forecast for 2027.

About this role

GiveDirectly works with Mobile Network Operators (MNO) to infer residence location from their data records to help target the poorest households and support emergency responses. We are hiring a Senior Data Scientist to progress this work on location inference from MNO data and make it repeatable.

Your job is to improve and extend our library of method templates, adapt them to each new operator and setting, and design new elements when an intervention requires it. You’ll assess what can be inferred from a given operator’s data, specify the analysis clearly enough for their data engineers to implement, then test it with them remotely or on site. You’ll support introductory meetings with MNOs and inform the work of data privacy and cybersecurity teams.

Reports to:

Senior Product Manager - MNO data

Level:

Senior Manager

Location: Remote, with substantial international travel (25-50% of time depending on emergencies). Hiring prioritized in: Cameroon, Canada, Colombia, DRC, Germany, Ghana, Kenya, Malawi, Mozambique, Netherlands, Nigeria, Poland, Portugal, Rwanda, South Africa, Spain, Turkey, Uganda, United Kingdom, and United States.

What you’ll do:

Improve and extend analytical method templates for establishing where people live from MNO data, and design novel methods when an intervention requires it

Support technical conversations with operators, bringing clarity on data needs and steering discussions toward workable technical designs

Assess information that can be inferred from each operator’s data given data types and sparsity

Write tests and method specifications for MNO data engineers to implement: steps, parameters, pseudocode, validation criteria

Guide operator engineering teams through implementation, in writing and in person

Run in-country workshops with operators to support new analyses and tune parameters based on statistical tests

Feed every new analytical and implementation element back into standard templates

Design for privacy from the start, using aggregation, minimization, and privacy-enhancing technologies such as private set intersection or homomorphic encryption

Protect confidentiality and improve internal data security processes

Build internal training material so technical and non-technical teams understand strengths and limits of this data source

What you’ll bring:

Exceptional alignment with GiveDirectly Values and active demonstration of core competencies: emotional intelligence, problem solving, project management, follow-through, and fostering inclusivity

Strong mathematical modeling, machine learning and statistics

Deep comfort with spatio-temporal data: temporal filtering, GIS, probability distributions, combinatorial reasoning, and working with sparse, irregular observations

Direct experience with Call Detail Records (CDRs) or latching data is a strong plus; comparable experience with mobility, transport, sensor or remote-sensing data counts

Ability to reason without ground truth

Pragmatism about the trade-off between accuracy and implementability

Excellent communication and relationship-building skills; ability to explain methods and limitations to multiple audiences

Experience writing technical specifications that other teams implemented

Able to read and review SQL and Python written by others; writing production-quality code yourself is welcome but not required

Commitment to privacy by design as foundational value; familiarity with privacy-enhancing technologies (private set intersection, secure multi-party computation, homomorphic encryption) is a strong plus

Commitment to confidentiality

Experience designing training material that changed how non-specialist colleagues used a data source

Comfort in fast-moving contexts where the brief may shift

Comfortable with travel to fragile and post-disaster contexts

Language Requirement: English

Language Preferences: French, Portuguese, Swahili or Spanish

Additional desirable experience:

poverty modeling; familiarity with survey data and survey instruments; experience inside a mobile network operator or working closely with one; open-source contributions in the mobility estimation space

About GiveDirectly

GiveDirectly has delivered more than $1B in cash directly to 2+ million people living in poverty and crisis across 15 countries. We’re growing fast and expect to hit $1B in revenue in 2026 with significant growth forecast for 2027.

About this role

GiveDirectly works with Mobile Network Operators (MNO) to infer residence location from their data records to help target the poorest households and support emergency responses. We are hiring a Senior Data Scientist to progress this work on location inference from MNO data and make it repeatable.

Your job is to improve and extend our library of method templates, adapt them to each new operator and setting, and design new elements when an intervention requires it. You’ll assess what can be inferred from a given operator’s data, specify the analysis clearly enough for their data engineers to implement, then test it with them remotely or on site. You’ll support introductory meetings with MNOs and inform the work of data privacy and cybersecurity teams.

Reports to:

Senior Product Manager - MNO data

Level:

Senior Manager

Location: Remote, with substantial international travel (25-50% of time depending on emergencies). Hiring prioritized in: Cameroon, Canada, Colombia, DRC, Germany, Ghana, Kenya, Malawi, Mozambique, Netherlands, Nigeria, Poland, Portugal, Rwanda, South Africa, Spain, Turkey, Uganda, United Kingdom, and United States.

What you’ll do:

Improve and extend analytical method templates for establishing where people live from MNO data, and design novel methods when an intervention requires it

Support technical conversations with operators, bringing clarity on data needs and steering discussions toward workable technical designs

Assess information that can be inferred from each operator’s data given data types and sparsity

Write tests and method specifications for MNO data engineers to implement: steps, parameters, pseudocode, validation criteria

Guide operator engineering teams through implementation, in writing and in person

Run in-country workshops with operators to support new analyses and tune parameters based on statistical tests

Feed every new analytical and implementation element back into standard templates

Design for privacy from the start, using aggregation, minimization, and privacy-enhancing technologies such as private set intersection or homomorphic encryption

Protect confidentiality and improve internal data security processes

Build internal training material so technical and non-technical teams understand strengths and limits of this data source

What you’ll bring:

Exceptional alignment with GiveDirectly Values and active demonstration of core competencies: emotional intelligence, problem solving, project management, follow-through, and fostering inclusivity

Strong mathematical modeling, machine learning and statistics

Deep comfort with spatio-temporal data: temporal filtering, GIS, probability distributions, combinatorial reasoning, and working with sparse, irregular observations

Direct experience with Call Detail Records (CDRs) or latching data is a strong plus; comparable experience with mobility, transport, sensor or remote-sensing data counts

Ability to reason without ground truth

Pragmatism about the trade-off between accuracy and implementability

Excellent communication and relationship-building skills; ability to explain methods and limitations to multiple audiences

Experience writing technical specifications that other teams implemented

Able to read and review SQL and Python written by others; writing production-quality code yourself is welcome but not required

Commitment to privacy by design as foundational value; familiarity with privacy-enhancing technologies (private set intersection, secure multi-party computation, homomorphic encryption) is a strong plus

Commitment to confidentiality

Experience designing training material that changed how non-specialist colleagues used a data source

Comfort in fast-moving contexts where the brief may shift

Comfortable with travel to fragile and post-disaster contexts

Language Requirement: English

Language Preferences: French, Portuguese, Swahili or Spanish

Additional desirable experience:

poverty modeling; familiarity with survey data and survey instruments; experience inside a mobile network operator or working closely with one; open-source contributions in the mobility estimation space

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Source and provenanceSource: BrighterMonday Kenya. Last checked: 2026-11-02.Kazi Connect is a job discovery service, not the employer. Always confirm the vacancy at the original source.Summaries may be AI-assisted. Report inaccurate content.
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