744 Research Director jobs in Kenya

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.

On behalf of
Huawei
, we are excited to announce an opportunity for a talented and motivated
Data Analyst
to join their dynamic team.

Responsibilities:

• Responsible for supporting digital operations and promoting digital platform operations in Southern African Region and representative offices.
• Lead the end-to-end data lifecycle, from sophisticated data cleansing and modeling to in-depth analysis and visualization, directly supporting frontline business expansion.
• Drive the deployment, adoption, and continuous improvement of digital platforms and data capabilities for digital transformation among representative offices and partners
• Basic understanding on ICT field, with knowledge of the technical architecture and business logic of carrier networks. Familiar with enterprise IT architecture and ICT industry trends is preferred.
• Proficient in data analysis methodologies, statistical principles, and data visualization.

Education Requirement:

• Bachelor's degree in Data Science, Computer Science, Information Systems, Statistics, Mathematics, or a related field.
• A postgraduate qualification or relevant professional certification (e.g., Microsoft Power BI, Tableau, or Data Analytics) will be considered an advantage.
• Strong verbal and written communication skills.
• Proficient in data manipulation and analysis programming languages (e.g., SQL, Python/R), with a proven ability to architect analytical logic and develop robust data solutions. Hands-on experience with leading BI and visualization tools (e.g., Tableau, Power BI) is highly desirable.
• experience in enterprise knowledge management, as well as designing and executing specialized operational projects is preferred.

Additional:

• English is the working language. Proficiency in Chinese will be considered an advantage.
• Proactive, with strong teamwork skills and able to work well under pressure.

• Develop and implement advanced analytical models to optimize supply chain and warehousing operations.
• Lead the collection, cleaning, and analysis of large datasets from various supply chain sources.
• Identify key performance indicators (KPIs) and create comprehensive dashboards for monitoring supply chain health.
• Conduct root cause analysis for supply chain disruptions and performance deviations.
• Develop demand forecasting models to improve inventory accuracy and reduce stockouts/overstocking.
• Optimize transportation routes and logistics networks for cost and efficiency.
• Collaborate with operations teams to enhance warehouse layout, workflow, and resource allocation.
• Utilize statistical software, machine learning techniques, and data visualization tools to derive insights.
• Present complex analytical findings and actionable recommendations to senior leadership.
• Mentor and guide a team of junior analysts and supply chain professionals.
• Stay abreast of industry trends and emerging technologies in supply chain analytics.
• Drive continuous improvement initiatives based on data-driven insights.

• Master's degree in Supply Chain Management, Operations Research, Data Science, Statistics, or a related quantitative field.
• Minimum of 7 years of experience in supply chain analytics, logistics, or operations management, with at least 3 years in a management capacity.
• Proven expertise in statistical analysis, predictive modeling, and data mining techniques.
• Proficiency in data analysis and visualization tools such as Python (Pandas, NumPy, Scikit-learn), R, SQL, Tableau, or Power BI.
• Strong understanding of supply chain principles, including inventory management, forecasting, and transportation.
• Excellent leadership, communication, and presentation skills.
• Ability to translate complex data into clear, actionable business recommendations.
• Experience in managing remote teams and projects is highly advantageous.

• Developing and implementing a comprehensive people analytics strategy aligned with organizational goals.
• Designing, building, and maintaining HR dashboards and reports using various BI tools.
• Conducting advanced statistical analyses on employee data, including predictive modeling and trend forecasting.
• Identifying key HR metrics and KPIs to measure the effectiveness of HR programs and initiatives.
• Translating complex data findings into clear, concise, and actionable insights for leadership and HR teams.
• Collaborating with HR business partners and functional leaders to understand their data needs and provide analytical support.
• Ensuring data accuracy, integrity, and compliance with privacy regulations.
• Staying current with the latest trends and technologies in HR analytics and data science.
• Developing and delivering training sessions on HR data interpretation and utilization.
• Driving a data-centric culture within the HR department and the wider organization.

• Develop and implement advanced analytics strategies to optimize supply chain operations, including inventory management, transportation, and warehousing.
• Design, build, and maintain comprehensive dashboards and reports to track key performance indicators (KPIs) across the supply chain.
• Utilize statistical modeling and machine learning techniques to forecast demand, identify trends, and predict potential disruptions.
• Analyze complex datasets to identify opportunities for cost reduction, efficiency improvements, and service level enhancements.
• Collaborate closely with logistics, warehousing, and operations teams to understand their analytical needs and provide data-driven solutions.
• Develop and implement data quality standards and ensure the accuracy and reliability of supply chain data.
• Present findings and recommendations to senior management and cross-functional teams, translating complex data into clear business insights.
• Stay abreast of the latest advancements in supply chain analytics tools and methodologies.
• Mentor and guide junior analysts within the remote team.
• Champion a data-driven culture throughout the supply chain organization.

• Master's degree in Supply Chain Management, Data Science, Statistics, Operations Research, or a related quantitative field.
• A minimum of 7-9 years of experience in supply chain analytics, operations research, or a similar analytical role.
• Proven experience in developing and implementing advanced analytical models and dashboards for supply chain optimization.
• Expertise in data analysis tools and programming languages such as SQL, Python, R, and BI tools (e.g., Tableau, Power BI).
• Strong understanding of supply chain processes, including inventory management, warehousing, transportation, and logistics.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional communication and presentation skills, with the ability to effectively convey complex data insights to diverse, remote audiences.
• Experience working with large datasets and distributed data platforms.
• Ability to work independently, manage multiple projects, and prioritize effectively in a remote setting.
• Experience in predictive modeling and forecasting techniques is highly desirable.
• Knowledge of supply chain operations relevant to the region of Thika, Kiambu, KE would be an asset.

• Designing and deploying sophisticated statistical models and machine learning algorithms to analyze player performance, team tactics, and game outcomes.
• Collecting, cleaning, and processing large datasets from diverse sources, ensuring data integrity and accuracy.
• Collaborating closely with coaching staff, scouting departments, and management to translate complex data insights into actionable recommendations.
• Developing custom dashboards and visualization tools to communicate key findings effectively to both technical and non-technical stakeholders.
• Staying abreast of the latest trends and advancements in sports analytics, data science, and relevant technologies.
• Mentoring and guiding junior analysts, fostering a culture of continuous learning and innovation.
• Conducting predictive analysis for player recruitment, injury prevention, and strategic planning.
• Ensuring the ethical and secure handling of all sensitive data.
• Presenting findings and strategic proposals in clear, concise formats during virtual team meetings.

• Leading and mentoring a team of sports analysts.
• Developing and implementing advanced analytical models for athlete and team performance.
• Designing data collection protocols and ensuring data integrity.
• Identifying key performance indicators and providing strategic recommendations.
• Translating complex data findings into clear, actionable insights for coaches and athletes.
• Collaborating with sports science, coaching, and medical staff.
• Staying current with the latest trends in sports analytics and technology.
• Presenting findings and recommendations to senior management.
• Managing the analytics technology stack and ensuring its effectiveness.

• Master's or Ph.D. in Statistics, Data Science, Sports Science, or a related quantitative field.
• At least 8 years of experience in sports analytics, with a significant portion in a leadership role.
• Expertise in statistical modeling, machine learning, and predictive analytics.
• Proficiency in data analysis tools and programming languages (e.g., Python, R, SQL).
• Experience with sports-specific data sources and analytical techniques.
• Strong understanding of athletic performance principles and various sports.
• Excellent leadership, communication, and presentation skills.
• Proven ability to work effectively in a fully remote and collaborative environment.