334 Lead Research Scientist Bioinformatics jobs in Nairobi

• Lead the design, development, and implementation of bioinformatics pipelines for analyzing genomic, transcriptomic, and proteomic data.
• Manage and mentor a team of bioinformatics scientists, fostering a collaborative and innovative research environment.
• Oversee multiple research projects, ensuring scientific accuracy, adherence to timelines, and efficient resource allocation.
• Develop and apply advanced statistical and computational methods to complex biological datasets.
• Collaborate with cross-functional research teams to define research questions and design experiments.
• Develop and maintain robust software tools and databases for data management and analysis.
• Evaluate and integrate new bioinformatics technologies and methodologies into existing workflows.
• Present research findings at scientific conferences and contribute to publications in peer-reviewed journals.
• Ensure data quality, integrity, and security throughout the research lifecycle.
• Contribute to grant writing and funding applications.

• Ph.D. in Bioinformatics, Computational Biology, Statistics, Computer Science, or a related field.
• Extensive experience in analyzing large-scale omics data (genomics, transcriptomics, etc.).
• Proven experience in leading and managing research teams.
• Strong programming skills in languages such as Python, R, and/or Perl.
• Proficiency with bioinformatics tools and databases (e.g., BLAST, Ensembl, UCSC Genome Browser).
• Experience with next-generation sequencing (NGS) data analysis workflows.
• Familiarity with cloud computing platforms (AWS, Google Cloud) and high-performance computing (HPC) environments.
• Excellent understanding of molecular biology principles.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills, with the ability to effectively present complex scientific information.

• Design, develop, and implement advanced bioinformatics pipelines for analyzing large-scale omics data (genomics, transcriptomics, proteomics).
• Lead bioinformatics efforts for specific research projects, from experimental design to data interpretation.
• Analyze and interpret complex biological datasets to identify significant findings and generate hypotheses.
• Collaborate with experimental biologists, clinicians, and other researchers to address scientific questions.
• Develop and maintain high-quality, reproducible computational workflows.
• Mentor and guide junior bioinformatics scientists and research staff.
• Stay current with the latest advancements in bioinformatics tools, algorithms, and methodologies.
• Contribute to manuscript preparation and grant writing.
• Manage computational resources and ensure efficient use of computing infrastructure.
• Present research findings at scientific meetings and conferences.

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related field.
• Strong publication record in peer-reviewed journals.
• Extensive experience in scripting languages such as Python or R for data analysis.
• Proficiency in statistical analysis and machine learning techniques.
• Experience with high-performance computing clusters and parallel processing.
• Familiarity with cloud computing platforms (AWS, GCP, Azure).
• Expertise in analyzing genomic, transcriptomic, or proteomic data using standard bioinformatics tools (e.g., GATK, STAR, DESeq2).
• Excellent problem-solving skills and a rigorous scientific approach.
• Strong communication and collaboration skills, with the ability to work effectively in a remote team.
• Prior experience in a leadership or mentoring role is an advantage.

• Design and implement computational strategies for the analysis of large-scale biological datasets (genomics, transcriptomics, proteomics, etc.).
• Develop and maintain bioinformatics pipelines and software tools for data processing, analysis, and visualization.
• Perform statistical analysis and machine learning to identify patterns, correlations, and predictive models in biological data.
• Interpret complex results and provide biological insights to research teams.
• Collaborate with experimental biologists to define research questions and design appropriate computational approaches.
• Stay current with the latest advancements in bioinformatics, computational biology, and relevant biological fields.
• Contribute to the writing of research manuscripts, grant proposals, and technical documentation.
• Manage and curate biological databases.
• Mentor junior bioinformaticians and research staff.
• Present findings at scientific conferences and internal meetings.

• Ph.D. or Master's degree in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
• Minimum of 6 years of hands-on experience in bioinformatics or computational biology research.
• Proven expertise in analyzing large-scale omics data (e.g., NGS data).
• Proficiency in programming languages commonly used in bioinformatics (e.g., Python, R, Perl).
• Experience with bioinformatics databases, tools, and algorithms (e.g., BLAST, GATK, etc.).
• Strong understanding of statistical methods and machine learning techniques.
• Familiarity with high-performance computing environments (e.g., HPC clusters, cloud computing).
• Excellent problem-solving, critical thinking, and analytical skills.
• Strong communication and collaboration skills, essential for a remote team environment.
• Publications in peer-reviewed journals are highly desirable.

• 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.

• 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.

• 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.

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.