1,479 Data Scientist jobs in Kenya

Job Description/Requirements
JOB SUMMARY

RequirementsBachelors or master's in computer science, machine learning, or related field  5+ years of industry experience working on data scientist with a focus on data modelling, stakeholder management and data mining., Proficiency using machine learning frameworks like keras, pytorch, Tensorflow, sckit-learn, statistical tools (statistical tests, distribution, regression, maximum likelihood estimators, strong math skills (multivariate calculus, linear algebra), machine learning methods (k-Nearest Neighbours, Naive Bayes, SVm, Decision forests), Data visualization tools (matplotlib, , Tableau). Experience working with structured and unstructured data using Python, R, Scala, Java, SQL in addition to one or more of Spark/Hadoop/Hive/HDFS , Apache Airflow, RabbitMQ/Kafka, Spark, Kubernates, and dbt. Working knowledge of databases, data systems, and analytics solutions, including proficiency in SQL, NoSQL, Java, Spark and Amazon Redshift for reporting and dashboard building. Experience with implementing unit and integration testing.

Responsibilities
Data Mining (20%): Design and implement robust data mining models to support analytics and reporting requirements. Carry out pre – processing, cleansing, and validating the integrioty of data to be used for analysis Enhance data collection procedures to include all relevant information for developing analytic systems. Statistical modelling (70%) Use statistical and machine learning techniques to develop solutions to support business operations from sales to credit collection. Stakeholder management (10%) Communicate results with stakeholders within the business operations teams.

Required Skills
Tax management, Cost tracking, analysis, Data analysis, Statistics, Data science, Reporting

Required Education
Bachelor's degree

Location:

Nairobi, Kenya (Hybrid/Remote options available)

Reports to:

Data Science Manager

About Pezesha

Pezesha is a leading embedded finance company that provides affordable and data-driven credit solutions to MSMEs across Africa. We combine technology, alternative data, and financial partnerships to close the $360B financing gap for small businesses while ensuring sustainable financial inclusion.

We are looking for a
Senior Data Scientist

to join our team and lead the development of advanced credit risk models, strategic insights, and business intelligence tools that drive high repayment rates, operational efficiency, and portfolio growth. This role is critical in strengthening our risk management framework and scaling our impact across the continent.

Core Responsibilities

Credit Risk Model Development

• Develop, test, and iterate credit risk models on a quarterly basis.
• Ensure repayment rates consistently exceed
  95%

, with a default rate of less than
3%

across all portfolios.

Strategic Data Insights

• Provide data-driven insights and reports to portfolio leads, senior management, and external stakeholders.
• Translate findings into actionable strategies to enhance performance and mitigate risks.

Data Extraction, Cleaning & Mining

• Lead the end-to-end processes of data extraction, cleaning, transformation, and mining.
• Build datasets that power descriptive, predictive, and spatial models to support decision-making.

Cross-Functional Experimentation

• Design and lead experiments across business units to optimize products, processes, and risk strategies.
• Measure and communicate results to ensure learnings drive continuous improvements.

Business Intelligence Development

• Develop and enhance BI tools to maximize product efficiency, improve Lifetime Value (LTV), and gross margins.
• Deliver at least two major BI tool enhancements or new feature implementations per quarter.

Real-Time Dashboards & Reporting

• Build and maintain real-time dashboards with a 99% uptime and accuracy target.
• Deliver monthly finance reports on-time and with > 99% accuracy in reports. Continuously add to exception reports to enhance portfolio quality and leverage AI + automation to improve reporting processes.
• Ensure accurate and timely lender reporting, portfolio impact analysis, and internal business reporting.

Documentation & Transparency

• Maintain clear documentation of models, experiments, and workflows to ensure reproducibility and transparency.

Mentorship & Team Leadership

• Mentor junior data scientists and analysts, fostering a collaborative, learning-driven culture.
• Lead the data science team in setting priorities, managing workloads, and delivering high-quality outputs.

Task Delegation & Ad Hoc Priorities

• Execute tasks assigned by the
  CEO, COO, Data Science Manager or CDO

, prioritizing based on organizational goals and impact.

Key Performance Indicators (KPIs)

• LMS Accuracy:

Achieve and maintain ≥
98% accuracy

in Learning Management System data validation.
- Sprint Completion:

Deliver
90%+ completion rate

for planned sprints on time.
- SLA Adherence:

Maintain
95%+ adherence

to Service Level Agreements (SLAs) across data services.
- Knowledge Transfer:

Deliver and track
quarterly KT sessions

and training for the data team.
- Credit Risk Model Performance:

Maintain
95% repayment rate

and <
3% default rate

via model iterations.
- Business Intelligence:

Deliver at least
2 new BI enhancements/features per quarter

to improve reporting and decision-making.

Qualifications & Skills

• Master's or higher in Data Science, Statistics, Computer Science, Economics, or related field.
• 6+ years of proven experience in data science, machine learning, and credit risk modeling (preferably in fintech or financial services).
• Strong expertise in Python, R, SQL, and big data tools.
• Experience with machine learning frameworks (TensorFlow, Scikit-learn, XGBoost, etc.).
• Proficiency in data visualization tools (PowerBI, ggplot, or plotly).
• Strong understanding of credit risk management, repayment behavior, and portfolio analytics.
• Excellent leadership, mentoring, and cross-functional collaboration skills.
• Strong communication skills with the ability to translate complex data into actionable insights.

Why Join Pezesha?

• Be part of a mission-driven company enabling financial inclusion for MSMEs across Africa.
• Work with a high-impact, data-driven team solving real-world financial challenges.
• Opportunities for growth, leadership, and regional exposure in a fast-scaling fintech.
• Competitive compensation and benefits package.

To Apply:

Please send a single pdf file containing a brief and bullet-pointed Cover Letter and your CV on the subsequent page(s) with "Ref: 2025-
Senior Data Scientist
" as the subject of your email to Interviews will be done on a rolling basis. In your application kindly add/attach the information below to

• At least one related project that you have worked on and accessible on Github
• Attach your up to date CV

Founded in 2018, Gozem is today a technological group of more than 400 people,
agile and ambitious
, which offers via its mobile application a very wide range of services including transport, delivery, financing, mobile money and many others, to African users. Present in Benin, Togo, Gabon and Cameroon, our group's ambition is to become "Africa's Super App" by establishing itself throughout French speaking Africa. Our solution is 100% focused on the African market, serving drivers, customers, traders and soon, SMEs in our areas of activity.

We are a multinational group, with a strong presence in several cities and pride ourselves on
helping to improve the lives of local communities
through the digitalisation of the market and the introduction of technology-based efficiencies.

Are you looking to grow in a challenging and friendly environment? Do you want to evolve and progress in dynamic and disruptive digital contexts?

Join us in building a new African digital ecosystem that improves the quality of life.
Together, let's make Africa smile
Website:

Google Play Store:

Apple App Store:

Glassdoor:

What is a Senior Data Scientist at Gozem?
At Gozem, our Senior Data Scientist is a strategic role at the intersection of
data science, applied machine learning, and fintech innovation
. In the Gozem Money business, you will design and implement advanced models to analyze transactional and behavioral data, predict outcomes, detect risks, and unlock new growth opportunities.

This role goes beyond model-building: you will take ownership of the
end-to-end data science workflow
, including fetching and cleaning data from diverse sources, building scalable models, and deploying them in production. You will collaborate closely with business leaders, engineers, and product managers to translate complex datasets into actionable insights that shape financial inclusion in Sub-Saharan Africa.

As a senior member of the data team, you will also mentor junior team members, contribute to our data culture, and play a key role in
ensuring insights quality, governance, and reliability
across our pipelines.

Your Tasks

• Build and deploy advanced statistical, machine learning, and AI models for use cases such as fraud detection, credit scoring, customer segmentation, churn prediction, and personalization.
• Design and implement analytics pipelines: clean, structure, and consume raw data from our data lakehouse, and other sources.
• Lead data-driven decision-making: collect, transform, analyze, and communicate insights that directly inform product, risk, and growth strategies.
• Manage and deliver data science projects from conception to production, ensuring alignment with business objectives.
• Collaborate with cross-functional teams (Product, Engineering, Operations, Finance) to translate business problems into data solutions.
• Monitor and optimize the performance of models and pipelines, ensuring the related solutions remain reliable, fair, and scalable.
• Mentor junior data scientists and analysts, providing guidance on best practices and methodologies.
• Stay up-to-date with the latest advances in AI/ML, MLOps, and fintech analytics, and help integrate them into Gozem's stack.

You are the right person for this job if you .

• Have strong expertise in machine learning, statistical analysis, and predictive modeling, and know how to bring models from prototype to production.
• Have hands-on experience with transactional data, financial services data, or digital payments.
• Are comfortable with basic analytics engineering tasks: writing efficient SQL queries, cleaning large messy datasets, and automating data flows.
• Have experience working with metadata standards, insights quality frameworks, and governance practices.
• Are able to communicate complex technical concepts clearly to non-technical stakeholders and influence decision-making.
• Can balance innovation with pragmatism, delivering models and insights that drive measurable business impact.
• Thrive in a fast-paced environment, taking ownership of challenges and moving projects forward.

You have

• Education: Bachelor's/Master's degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.
• Experience: 5+ years of experience in data science, preferably in fintech, banking, payments, or digital platforms.
• Core skills: Mastery of SQL, Python, and ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Analytics engineering basics: Experience with ETL & automation tools (Airflow, Dataform, or equivalent), and handling large-scale structured/unstructured datasets.
• Visualization: Proficiency in Looker Studio, Metabase, or other BI tools.
• Nice-to-have skills: Knowledge of R, BigQuery, GCP, or MLOps frameworks (MLflow, Kubeflow, etc.).
• Tools to master: Asana, Jira, Google Suite.
• Languages: French and/or English (bilingual proficiency is a strong plus).
• Location: Hybrid.

What We Like Most

• Self-motivated, autonomous, and proactive in identifying opportunities to create value with data.
• A natural mentor who enjoys helping others grow.
• Detail-oriented, structured, and able to manage time efficiently in a fast-paced, multi-market environment.
• Excited about the challenge of using data to transform financial services in Africa.

Working Conditions & Benefits
We offer our employees a fair, friendly and intercultural working environment, in which we strive to develop the talents of each individual. To achieve this, we offer:

Open-space offices and teleworking time possible (to be arranged with your manager)

A gross monthly remuneration defined according to our internal salary grid as well as the relevance of your past experiences for the position.

An option to buy shares in Gozem

An annual bonus allowing you to receive between 0 and 4.5 months of additional salary the following year

Benefits on our Super App for your travel and deliveries

A health and IT insurance package

And above all, the opportunity to join a young, dynamic team that has a real social impact in French-speaking Africa
Interview process

• An initial introductory meeting with the recruitment manager (15 minutes)
• A written interview questionnaire
• A business case to be completed within 07 days
• A presentation of your business case with the head of the Data team (future n+1) and a time to discuss your professional experience followed by a referral request (you give us 4 professional contacts to whom we send a questionnaire)
• One final validation interview with one of our co-founders

• Assist in collecting, cleaning, and preparing large datasets for analysis.
• Perform exploratory data analysis to identify patterns, trends, and insights.
• Develop and implement statistical models and machine learning algorithms under guidance.
• Support the development of data visualizations to communicate findings effectively.
• Collaborate with senior data scientists on various projects and research initiatives.
• Learn and apply various data mining techniques and tools.
• Document code, methodologies, and findings meticulously.
• Participate in team meetings and contribute to discussions on data-related challenges.
• Assist in the testing and validation of predictive models.
• Gain exposure to cloud computing platforms and big data technologies.
• Contribute to the continuous learning and development within the data science team.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Strong foundational knowledge of statistics, machine learning, and data mining concepts.
• Proficiency in at least one programming language commonly used in data science (e.g., Python, R).
• Familiarity with data manipulation libraries (e.g., Pandas, NumPy).
• Basic understanding of database querying languages (e.g., SQL).
• Excellent analytical and problem-solving abilities.
• Strong communication skills, both written and verbal.
• Eagerness to learn and adapt to new technologies and methodologies.
• Ability to work independently and collaboratively in a remote setting.
• Enthusiasm for data and its potential to drive business value.

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field, obtained within the last 12 months.
• Strong understanding of statistical concepts and machine learning algorithms.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Experience with data manipulation and analysis tools.
• Familiarity with data visualization techniques and tools.
• Excellent analytical and problem-solving skills.
• Strong written and verbal communication skills for remote collaboration.
• Ability to work independently and manage time effectively in a remote setting.
• Eagerness to learn and adapt to new technologies and methodologies.
• Previous internship or project experience in data science is a plus.

• Assist in collecting, cleaning, and preprocessing large and complex datasets from various sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Develop and implement machine learning models under the guidance of senior data scientists.
• Evaluate the performance of developed models and provide insights for improvement.
• Create compelling data visualizations to communicate findings and insights to stakeholders.
• Contribute to the documentation of data science processes, methodologies, and results.
• Collaborate with team members on ongoing data science projects.
• Learn and apply new data analysis techniques and tools.
• Assist in the deployment and monitoring of machine learning models.
• Participate in team meetings and brainstorming sessions to generate new ideas.
• Support the team in ad-hoc data-related requests and analyses.

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
• Strong understanding of fundamental statistical concepts and machine learning algorithms.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) is a plus.
• Familiarity with SQL for data querying and manipulation.
• Excellent analytical and problem-solving skills.
• Strong communication skills, both written and verbal, with the ability to explain technical concepts.
• Ability to work independently and manage time effectively in a remote setting.
• A strong desire to learn and grow in the field of data science.
• Previous internship or project experience in data analysis or machine learning is advantageous.