377 Analytical jobs in Nairobi

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.

A Business Data Analytics and Research intern plays a crucial role in organizations by leveraging data to drive strategic decision-making, conducting research to identify market trends, and optimizing business operations. Below are key responsibilities and skills typically associated with this role:

Key Responsibilities:

1. Data Collection and Analysis
   :

2. Gather and analyze business, market, and financial data from various sources to provide insights into performance and trends.

3. Use statistical tools to interpret data sets, identifying patterns and trends that inform business decisions.

2.Data Visualization, Reporting and Presentation
:

• Prepare and present detailed reports, dashboards, and visualizations that summarize key data insights and findings.
• Communicate complex data results to non-technical stakeholders in a clear and actionable manner.
• Capacity to develop concept notes and proposals based on market research gaps

3. Market Research
:

• Conduct qualitative and quantitative research to identify new market opportunities, competitor analysis, and customer preferences.
• Evaluate market conditions, industry trends, and competitors' activities to support business growth strategies.
• Prepare presentations based on market research reports

4.Business Performance Monitoring
:

• Monitor key performance indicators (KPIs) to track business progress and identify areas for improvement.
• Recommend improvements based on data insights to optimize processes, reduce costs, and increase profitability.

5.Collaborating with Teams
:

• Work closely with different departments such as marketing, finance, and operations to align data-driven insights with business objectives.
• Provide support for product development, sales strategies, and customer experience initiatives through data analysis.

6.Data Management
:

• Ensure the accuracy, completeness, and security of data.
• Develop and maintain databases, data collection systems, and strategies for efficient data storage and retrieval.

Key Skills:

1.Data Analytics Tools
:

• Proficient in tools like SQL, Excel, Tableau, Power BI, Google Analytics, and other business intelligence platforms.

2.Statistical Analysis
:

• Knowledge of statistical software (e.g., R, SAS, SPSS) and techniques such as regression analysis, hypothesis testing, and predictive modeling.

3.Research and Excellent Writing skills:

• Strong ability to conduct both primary and secondary research, including surveys, interviews, and literature reviews.
• Capacity to develop report and concepts based on market research reports

4.Problem-Solving
:

• Analytical thinking to identify issues, trends, and opportunities through data, and propose actionable solutions.

5.Communication Skills
:

• Excellent written and verbal communication skills to present findings and recommendations clearly to stakeholders.

6.Attention to Detail
:

• High level of precision in handling large data sets and ensuring data accuracy.

7.Project Management
:

• Ability to manage multiple research projects simultaneously, ensuring timely delivery of results.

Education, knowledge and experience:

• A degree in Agricultural Economics or a related field.
• Experience in management and analysis of data.
• Field experience and synthesis of data and lessons for learning
• Knowledge and savvy of data analysis software, especially Stata.
• Very strong analytical skills and applied statistical experience.
• Good scientific wring experience.

Our client is a multinational financial services firm, with a significant footprint.

Based in either Nairobi or Kuala Lumpur, this role will play a critical role in supporting their internal audit activities by providing insights through the analysis and correlation of data extracted from various systems across the business. Through advanced data analytics techniques, the role will enable the audit team to identify control failures, assess risks, and provide independent assurance to senior leadership that risks are being managed effectively and remain within the organization's approved risk appetite.

Key analytical activities include:

• Data profiling:
  Generating statistics to provide context and background on business processes.
• Reperformance testing:
  Re-performing calculations to validate transactions (e.g., payroll, claims), metrics from management information reports, and analytics models.
• Exception detection:
  Identifying instances where known restrictions, policies, or guidelines have not been followed.
• Anomaly detection:
  Detecting unusual or unexpected patterns of behaviour through data analysis.
• Root cause analysis:
  Identifying and quantifying the factors contributing to control failures and providing actionable insights.

The role also supports the internal audit leadership team in assessing the overall effectiveness of risk management practices.

Scope of the Role

As part of the regional audit resource pool, the Data Analytics Manager will be responsible for:

• Applying data analytics tools such as
  SQL
  and
  Python
  to support audit teams across the full audit lifecycle, from planning through closure.
• Detecting symptoms of control failures by analyzing operational data and providing insights to audit leads.
• Developing and maintaining
  continuous auditing dashboards
  using visualization tools such as
  Tableau
  or
  Power BI
  , providing clear visibility of control effectiveness across business units.
• Identifying trends and emerging themes that support the development of opinions on the organization's overall control environment.
• Supporting leadership in delivering continuous improvement initiatives and meeting stakeholder reporting requirements.
• Collaborating with internal teams, including
  IT
  and
  Compliance
  , to facilitate efficient data sourcing for audits and analytics initiatives.

Key Accountabilities

• Build and maintain strong working relationships with audit directors, internal audit leadership, and operational management teams.
• Deliver analytics outputs in line with internal methodologies and audit timelines.
• Provide audit leads with timely, accurate data-driven insights during fieldwork.
• Present audit findings to senior management, ensuring that appropriate responses are obtained for each identified issue.
• Manage analytics projects effectively, taking ownership of deliverables from start to finish.

Core Competencies

• Strong technical skills with
  SQL
  and
  Python (Pandas Library)
  for data analytics.
• Proficiency in visualization tools such as
  Tableau
  and/or
  Power BI
  .
• Advanced knowledge of
  Python
  /
  R
  for text analytics, NLP, predictive analytics, or machine learning is highly desirable.
• Excellent stakeholder management, communication, and presentation skills.

Knowledge & Experience

• Hands-on technical experience
  mining, cleaning, and analyzing data using databases and analytics tools.
• Strong working knowledge of SQL in a relational database environment.
• Solid experience using Python for data analysis and automation.
• Experience with machine learning and predictive analytics is advantageous.
• Background in
  financial services
  preferred, ideally with exposure to
  insurance
  or
  investment management
  sectors.
• Experience working within an
  audit
  or
  risk management
  environment is highly desirable.
• Exceptional attention to detail and logical problem-solving abilities.
• A collaborative team player with the ability to build and maintain professional respect within the team and across departments.

• Recent graduate with a Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Engineering, or a related discipline.
• Strong analytical and problem-solving skills.
• Proficiency in basic statistical concepts.
• Familiarity with data analysis tools and/or programming languages (e.g., Excel, SQL, Python, R) is a plus.
• Excellent written and verbal communication skills.
• Ability to work independently and manage time effectively in a remote setting.
• A strong desire to learn and develop skills in data analytics.
• Good teamwork and collaboration abilities.

• Develop and implement advanced statistical models and machine learning algorithms.
• Analyze large, complex datasets to identify trends, patterns, and actionable insights.
• Design and conduct experiments to test hypotheses and evaluate model performance.
• Build predictive models for forecasting, customer segmentation, and risk assessment.
• Collaborate with business stakeholders to define analytical requirements and project goals.
• Develop and maintain data pipelines and ETL processes.
• Communicate complex analytical findings and recommendations to diverse audiences.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Mentor junior data scientists and contribute to the team's technical growth.
• Ensure the ethical use of data and compliance with privacy regulations.

• Ph.D. or Master's degree in Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Minimum of 8 years of experience in data science, with a strong track record of developing and deploying predictive models.
• Proven experience leading data science projects and teams in a remote setting.
• Expertise in statistical modeling, machine learning techniques (e.g., regression, classification, clustering, deep learning), and data mining.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong SQL skills and experience with big data technologies (e.g., Spark, Hadoop).
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong communication and presentation skills, with the ability to explain complex concepts clearly.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Ability to manage multiple projects and deliver results in a fast-paced, remote environment.