338 Research Scientist jobs in Nairobi

• Collect and clean sports performance data from various sources, including wearable devices, video analysis, and statistical databases.
• Develop and implement statistical models and machine learning algorithms to identify trends, predict outcomes, and optimize performance.
• Analyze game footage and athlete movements to extract key performance indicators (KPIs).
• Translate complex data findings into clear, concise, and actionable insights for coaching staff and athletes.
• Create comprehensive reports and visualizations to communicate findings effectively.
• Collaborate with coaches and training staff to understand their needs and tailor analytical approaches.
• Stay current with the latest research and technologies in sports science, analytics, and performance optimization.
• Contribute to the development of new data collection and analysis methodologies.
• Ensure data integrity and confidentiality.
• Present findings and recommendations in a compelling manner to stakeholders.

• Design, develop, and implement HR analytics strategies and solutions.
• Analyze HR data to identify trends, patterns, and key drivers related to workforce planning, talent management, employee engagement, and retention.
• Develop and maintain HR dashboards and reports to visualize key metrics and insights.
• Conduct predictive modeling to forecast workforce needs, identify flight risks, and assess talent pipeline strength.
• Partner with HR business partners and leadership to understand business needs and translate them into analytical requirements.
• Communicate complex analytical findings and recommendations clearly to both technical and non-technical audiences.
• Ensure data integrity, accuracy, and compliance with data privacy regulations.
• Stay current with the latest trends and best practices in HR analytics and people data science.
• Advise on the strategic use of HR data to improve organizational effectiveness and employee experience.
• Collaborate with IT and data management teams to ensure robust data infrastructure.

• Master's degree in Human Resources, Statistics, Data Science, Business Analytics, or a related field.
• Minimum of 7 years of experience in HR analytics, people analytics, or a related data-focused HR role.
• Proven expertise in statistical analysis, predictive modeling, and data visualization tools (e.g., Tableau, Power BI, SQL, Python/R).
• Strong understanding of HR functions, including talent acquisition, talent management, compensation, performance management, and employee relations.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional written and verbal communication and presentation skills.
• Ability to work independently and manage multiple complex projects in a remote environment.
• Experience with HRIS systems (e.g., Workday, SAP SuccessFactors) is a plus.
• Demonstrated ability to influence stakeholders and drive data-informed decision-making.
• Strong ethical grounding and commitment to data privacy.

• Collect, clean, and process large datasets from various sports events and platforms.
• Develop and implement statistical models to analyze player performance, team strategies, and game outcomes.
• Create compelling data visualizations and reports to communicate findings to coaches, management, and other stakeholders.
• Identify key performance indicators (KPIs) and track progress towards strategic goals.
• Conduct predictive analysis to forecast game results, player development, and injury risks.
• Collaborate with coaching staff to translate data insights into practical game plans and training regimes.
• Stay abreast of the latest trends and advancements in sports analytics, data science, and related technologies.
• Develop and maintain databases and dashboards for real-time performance monitoring.
• Contribute to the development of innovative analytical tools and methodologies.
• Present findings and recommendations clearly and concisely to diverse audiences.
• Assist in scouting and player recruitment by analyzing potential talent based on performance metrics.

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Data Science, Sports Science, or a related quantitative field.
• Proven experience in sports analytics, data analysis, or a similar role.
• Proficiency in statistical programming languages such as R, Python, or SQL.
• Experience with data visualization tools like Tableau, Power BI, or Matplotlib.
• Strong understanding of statistical modeling, machine learning, and predictive analytics techniques.
• Deep knowledge of sports rules, strategies, and common performance metrics across multiple disciplines.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong communication and presentation skills, with the ability to explain complex data to non-technical audiences.
• Ability to work independently, manage time effectively, and collaborate remotely.
• Experience with the sports landscape in **Mombasa, Mombasa, KE** is a plus, but not mandatory for this remote position.

• Design, develop, and implement sophisticated statistical models and algorithms to analyze sports performance data.
• Identify trends, patterns, and insights that can enhance athletic performance, strategy, and fan experience.
• Collaborate with coaches and athletes to understand their data needs and provide tailored analytical support.
• Lead and mentor a team of junior sports analysts, fostering a culture of innovation and continuous learning.
• Develop and maintain robust data pipelines and ensure data integrity.
• Create compelling data visualizations and reports to communicate findings to diverse audiences.
• Contribute to the development of new analytical tools and platforms.
• Stay current with advancements in sports analytics, machine learning, and relevant technologies.
• Present findings and recommendations to senior management and key stakeholders.
• Manage multiple analytical projects concurrently, ensuring timely delivery and impactful results.

• Master's or Ph.D. in Statistics, Data Science, Sports Science, Mathematics, or a related quantitative field.
• Minimum of 8 years of experience in sports analytics or a related field, with a proven track record of leadership.
• Expertise in statistical modeling, machine learning techniques, and data mining.
• Proficiency in programming languages such as Python or R, and experience with SQL.
• Strong experience with data visualization tools (e.g., Tableau, Power BI).
• Deep understanding of various sports and their underlying performance metrics.
• Excellent communication and presentation skills, with the ability to explain complex data to non-technical audiences.
• Demonstrated ability to lead and manage a team in a remote setting.
• Strong problem-solving skills and a passion for sports innovation.

• Perform comprehensive financial statement analysis for publicly traded and private companies.
• Develop and maintain financial models, including discounted cash flow (DCF), comparable company analysis, and precedent transactions.
• Conduct industry and market research to identify trends, opportunities, and risks.
• Prepare detailed investment research reports, presentations, and memos for senior management and investment committees.
• Evaluate the financial performance and potential of investment opportunities across various sectors.
• Monitor macroeconomic factors and their potential impact on investment portfolios.
• Assist in due diligence processes for potential acquisitions or investments.
• Collaborate with portfolio managers and other stakeholders to provide analytical support.
• Stay current with financial regulations, market developments, and valuation methodologies.
• Ensure accuracy and integrity of all financial data and analyses.
• Present findings and recommendations clearly and concisely.

• Bachelor's degree in Finance, Economics, Accounting, or a related quantitative field.
• Proven experience as a Financial Analyst, Investment Analyst, or in a similar role within the banking or finance sector.
• Strong understanding of financial modeling, valuation techniques, and accounting principles.
• Proficiency in financial data analysis tools and software (e.g., Bloomberg Terminal, FactSet, Refinitiv Eikon).
• Excellent analytical, critical thinking, and problem-solving skills.
• Strong written and verbal communication skills, with the ability to present complex financial information effectively.
• Ability to work independently, manage multiple projects, and meet deadlines in a remote setting.
• Experience with Python, R, or other statistical programming languages is a plus.
• CFA charterholder or candidate progressing towards CFA is highly desirable.
• High ethical standards and attention to detail.

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.

• Lead and mentor a team of postdoctoral fellows, research assistants, and technicians in a remote setting.
• Design, develop, and implement cutting-edge research projects in areas such as oncology, infectious diseases, or neurobiology.
• Oversee experimental design, data collection, and rigorous data analysis.
• Secure research funding through competitive grant applications and collaborations.
• Publish research findings in high-impact, peer-reviewed scientific journals.
• Present research outcomes at international scientific conferences and internal meetings.
• Collaborate with internal and external collaborators, including industry partners, to advance research objectives.
• Ensure compliance with all laboratory safety protocols, ethical guidelines, and regulatory requirements.
• Manage research budgets, equipment, and resources effectively.
• Stay abreast of the latest scientific advancements and methodologies in the relevant field.

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.

• Analyze diverse biological datasets, including genomics, transcriptomics, proteomics, and metabolomics data.
• Develop, implement, and validate bioinformatics pipelines and algorithms for data analysis.
• Utilize statistical methods and machine learning techniques to identify patterns and derive biological insights.
• Collaborate closely with experimental scientists to design studies, interpret results, and contribute to manuscript preparation.
• Contribute to the development of new research hypotheses and experimental strategies.
• Manage and organize large biological datasets, ensuring data integrity and reproducibility.
• Develop custom scripts and software tools to support research needs.
• Stay current with the latest advancements in bioinformatics, computational biology, and relevant biological fields.
• Present research findings at scientific meetings and contribute to publications in peer-reviewed journals.
• Participate in grant writing efforts to secure funding for research projects.

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
• Minimum of 4-6 years of relevant research experience in bioinformatics or computational biology.
• Proficiency in programming languages such as Python and R, with experience in relevant libraries (e.g., Biopython, NumPy, SciPy, ggplot2).
• Experience with next-generation sequencing (NGS) data analysis.
• Solid understanding of statistical methods and machine learning algorithms.
• Familiarity with Unix/Linux operating systems and command-line tools.
• Experience with database management and query languages (e.g., SQL).
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Ability to work independently and collaboratively in a remote team environment.