491 Data Professionals jobs in Nairobi

• Assist in the collection, cleaning, and pre-processing of large datasets for AI model training.
• Support the development and implementation of machine learning models and algorithms under the guidance of senior researchers.
• Conduct exploratory data analysis to identify patterns and insights relevant to research objectives.
• Help in the evaluation and validation of model performance using various metrics.
• Contribute to the documentation of research findings, methodologies, and code.
• Participate in team meetings and brainstorming sessions to discuss project progress and future directions.
• Research and present relevant academic papers and industry trends in AI and ML.
• Assist in the preparation of research reports and presentations for internal and external audiences.
• Implement and test new AI techniques and frameworks.
• Collaborate with other interns and team members on assigned tasks.
• Ensure code is well-documented and follows best practices for reproducibility.
• Learn and apply advanced statistical and computational techniques relevant to AI research.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, or a related quantitative field.
• Solid understanding of fundamental machine learning concepts and algorithms.
• Proficiency in Python and experience with relevant libraries such as TensorFlow, PyTorch, scikit-learn, pandas, and NumPy.
• Familiarity with data manipulation and analysis techniques.
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills, both written and verbal, with the ability to articulate technical concepts clearly.
• Ability to work effectively in a remote, collaborative team environment.
• Eagerness to learn and adapt to new technologies and research challenges.
• Previous exposure to AI research projects or Kaggle competitions is a plus.
• Demonstrated passion for artificial intelligence and its applications.

Company Description
Infotrak Research and Consulting is a full service research company that was founded in 2004 following the vision of the founder to provide the Pan African Market with suitable information solutions required to sustain the ever-growing economies in the continent.

Headquartered in Nairobi, Kenya, Infotrak also has affiliate offices in Uganda, Tanzania, Nigeria and field contacts in more than 12 other countries in Sub Saharan Africa. The firm attributes its rapid growth to not only innovation, high level of professionalism and dynamism, but also on the excellent caliber of personnel who have been described by many as "Business minds who specialize in research".

Services provided include: Customer & Employee Satisfaction Surveys, Market Segmentation Studies, Brand Health checks, Consumer Usage and attitude studies, advertising awareness/impact surveys, advertising pre-post testing, media surveys, pricing studies, new product research, market feasibilities, formative research, perception surveys, KAP studies etc.

Job Description
We are seeking a highly skilled and detail-oriented Data Analyst with a minimum of five (5) years' experience in data analytics to join our dynamic team. The ideal candidate should have a strong background in statistical analysis, data management, and visualization.

Key Responsibilities:

• Process, clean, and validate large datasets from various sources.
• Prepare survey sampling designs.
• Perform statistical analysis and interpretations to identify trends, patterns, and correlations.
• Develop dashboards, reports, and data visualizations to support business objectives.
• Collaborate with cross-functional teams to understand data needs and provide analytical support.
• Apply advanced analytical techniques to solve complex problems.
• Ensure data integrity, confidentiality, and compliance with relevant policies and regulations.
• Implement process improvements and data-driven strategies to optimize performance.

Qualifications

• Bachelor's degree in Statistics or a related field. Master's degree will be an added advantage.
• Minimum of five (5) years' proven experience in data analytics, statistical modelling, and reporting.
• Proficiency in statistical tools and programming languages (e.g., SPSS, STATA, MS Excel, R, and Python).
• Strong experience with data visualization tools (e.g., Power BI, Tableau).
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong communication and presentation skills.
• Ability to work independently and as part of a team in a fast-paced environment.

Additional Information

This job is full time job and the applicant must be willing to work outside of the country.

If you meet the above requirements, send your CV with a cover letter and testimonials to

the contact address provided.

NB: Ladies are strongly encouraged to apply.

About CHANCEN International
Chancen International is a non-profit financial institution providing ethical, fair, and responsible financing to help young Africans access quality tertiary education. Using an innovative Income Share Agreement (ISA) model, we cover students' tuition fees, allowing them to study without financial barriers. Graduates repay a portion of their income once employed, creating a sustainable funding cycle that supports future generations. By empowering young people with education, we enable their transition to meaningful employment, fostering economic mobility and strengthening communities.

Headquartered in Kigali, Rwanda, and operating in Rwanda, Kenya, South Africa, and Ghana, Chancen International has helped over 5,000 young people access education leading to dignified work. Our focus on marginalized populations ensures these youth gain the skills needed to thrive and contribute to building strong economies and peaceful nations.

We are committed to creating an inclusive and positive working environment where each individual can flourish and achieve their full potential. Our actions are guided by our company values: Authenticity, Curiosity, Courage, Stewardship and Fairness.

**Job Summary

The Research & Data Specialist will play a key role in strengthening Chancen's ISA underwriting and portfolio analytics by ensuring high-quality data input, interpreting macroeconomic and market trends, and integrating external datasets. This role sits within the Financial Planning and Analysis team and supports pricing, risk analysis, and portfolio optimization efforts. The Specialist will work closely with the Tech, Finance, and Impact teams to improve how Chancen collects, organizes, and analyzes data across countries and portfolios.
Key Responsibilities**
1. Data Input & Quality Assurance

• Maintain standardized input templates (ISA, PEI, employment); enforce schema, validation, and audit trails.
• Run QA checks (completeness, outliers, duplicates, cohort consistency); reconcile discrepancies with data owners.

• Publish data quality reports and escalate recurring issues with corrective actions.

• Underwriting Support

• Ingest and harmonize PEI datasets (enrolment, completion, placement, salary distributions/percentiles).

• Compute placement rate, time-to-placement, salary progression curves by program/PEI/country.

• Produce quarterly PEI scorecards to inform pricing guardrails (share %, thresholds, caps) and affordability checks.

• Market & Macro Trend Analysis

• Track inflation, minimum wage, unemployment, sector demand, and youth income trends; maintain a macro indicator pack per country.

• Write concise insight briefs (one-pager) highlighting risk/opportunity and recommended parameter changes.

• Country Partnerships & Data Procurement

• Build strong working relationships with Country Managers, PEIs, ministries/labour bureaus, and relevant agencies across different countries.

• Map, source, and procure priority datasets (employment, wage, placement, census/sector data, PEI admin data); maintain a live source register with refresh cadences and owners.
• Lead data-sharing requests and negotiate MoUs/DSAs with support from Legal/Compliance; ensure licensing terms, usage rights, and privacy are respected.
• Set SLAs for delivery, quality, and format with country partners; monitor adherence and escalate risks early.

• Track procurement budget and cost per dataset; propose cost-effective alternatives when needed.

• Data Systems & Integration

• Align datasets to the data warehouse schema; define data contracts and SLAs with Tech.

• Co-build/maintain dashboards for portfolio health, outcomes, and underwriting inputs (BI tools).
• Version control for data artifacts, queries, and calculations; maintain data dictionary.

Requirements

Educational Qualifications
Minimum Bachelor's Degree in project management, analytics, Economics, Statistics, Applied Economics
Technical Skills, Competencies, and Experience

• Bachelor's in Economics, Data Science, Statistics, Finance, or related field.
• 3–5 years in research/data analysis/credit modelling or adjacent roles.
• Proven experience cleaning, joining, and analysing education/employment datasets and building BI dashboards.
• Familiarity with income-based repayment/loan portfolios/credit scoring is advantageous.
• Experience across African markets preferred; strong written and verbal communication.
• Experience collaborating with country teams and external data owners (government, PEIs, research firms).
• Working knowledge of data licensing, privacy, and DPAs (GDPR/local equivalents) is a plus.

• Conduct cutting-edge research in machine learning, deep learning, and related AI fields.
• Design, develop, and implement advanced AI algorithms and models for various applications.
• Prototype and experiment with new AI technologies, frameworks, and approaches.
• Analyze and interpret large datasets to train and validate AI models.
• Optimize model performance for scalability, efficiency, and accuracy.
• Collaborate with software engineers to integrate AI models into production systems.
• Stay abreast of the latest advancements in AI research and industry trends.
• Publish research findings in reputable conferences and journals.
• Mentor junior researchers and engineers, fostering a collaborative research environment.
• Contribute to the intellectual property strategy through invention disclosures and patent applications.
• Evaluate and select appropriate tools, libraries, and platforms for AI development.
• Ensure the ethical and responsible development and deployment of AI technologies.
• Participate in cross-functional team meetings and contribute to strategic planning.
• Develop clear and concise technical documentation for research projects and implemented solutions.
• Present research progress and findings to internal stakeholders and at external forums.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 7 years of progressive experience in AI/ML research and development.
• Proven track record of developing and deploying complex machine learning models (e.g., neural networks, NLP, computer vision).
• Expertise in programming languages such as Python, and proficiency with ML frameworks like TensorFlow, PyTorch, or Keras.
• Strong understanding of statistical modeling, data mining, and algorithm design.
• Experience with big data technologies (e.g., Spark, Hadoop) is highly desirable.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional communication and presentation skills, essential for remote collaboration and disseminating research.
• Ability to work independently, drive research initiatives, and manage projects effectively in a remote setting.
• Experience with cloud computing platforms (AWS, Azure, GCP) for ML workloads is a plus.
• Strong publication record in top-tier AI/ML venues is advantageous.

• Design, develop, and implement sophisticated machine learning models and algorithms to solve complex business problems.
• Conduct exploratory data analysis to identify patterns, trends, and insights from large and complex datasets.
• Perform feature engineering, model selection, training, validation, and hyperparameter tuning.
• Develop predictive and prescriptive models for applications such as forecasting, anomaly detection, recommendation systems, and natural language processing.
• Evaluate model performance, interpret results, and communicate findings clearly to technical and non-technical stakeholders.
• Collaborate with software engineers to deploy machine learning models into production environments.
• Stay abreast of the latest research and advancements in machine learning, AI, and related fields.
• Design and conduct experiments to test hypotheses and validate model effectiveness.
• Develop and maintain robust data pipelines for model training and inference.
• Mentor junior data scientists and contribute to the team's technical growth.
• Ensure data quality, integrity, and privacy throughout the data science lifecycle.
• Write clean, well-documented, and reproducible code, primarily in Python or R.
• Contribute to the development of intellectual property through research and innovation.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field with a focus on Machine Learning.
• Proven track record of conducting cutting-edge research and developing impactful machine learning models.
• Extensive experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong programming skills in Python or R, including experience with data manipulation libraries (e.g., Pandas, NumPy).
• Proficiency in SQL and experience working with various database systems.
• Deep understanding of statistical concepts, algorithms, and their practical application.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Superior communication and presentation skills, capable of explaining complex technical concepts to diverse audiences remotely.
• Ability to work independently, manage projects, and drive research initiatives from conception to completion.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) for machine learning is beneficial.