1,673 Data Manipulation jobs in Kenya

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Climate Change
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– integration, localization, and reporting

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– frameworks, tools, and impact measurement

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• Analyze and interpret geological, geophysical, and geochemical data from various sources.
• Conduct remote sensing data analysis and integrate with field data.
• Prepare detailed geological maps, cross-sections, and reports.
• Identify potential areas for mineral or resource exploration based on data analysis.
• Collaborate with exploration geologists and other technical experts.
• Manage and maintain geological databases.
• Develop and implement survey methodologies.
• Stay updated on the latest advancements in geological survey techniques and technologies.
• Provide technical guidance and support to exploration teams.

• Master's degree in Geology, Geophysics, Earth Sciences, or a related discipline.
• Minimum of 5 years of experience in geological surveying and data interpretation.
• Proficiency in geological software (e.g., ArcGIS, Leapfrog, Petrel) and remote sensing tools.
• Strong understanding of mineral exploration techniques.
• Excellent analytical and problem-solving skills.
• Ability to work independently and manage time effectively in a remote setting.
• Strong report writing and presentation skills.
• Experience in the mining sector, particularly in resource estimation, is highly desirable.

• Analyze geological survey data using specialized software.
• Interpret geophysical and geochemical data to identify mineral potential.
• Prepare detailed geological reports and presentations for stakeholders.
• Collaborate with exploration teams to plan and optimize survey methodologies.
• Assess the economic viability and technical feasibility of mining projects.
• Stay current with geological research, technologies, and industry best practices.
• Provide expert geological advice and recommendations.
• Maintain accurate and organized geological databases.
• Ensure compliance with environmental and safety regulations in data interpretation.

• Master's degree or Ph.D. in Geology, Geophysics, or a related field.
• Minimum of 7 years of relevant experience in geological surveying and data analysis.
• Proficiency in geological modeling and visualization software (e.g., ArcGIS, Leapfrog, Petrel).
• Strong understanding of mineral exploration techniques and mining processes.
• Excellent analytical, problem-solving, and research skills.
• Exceptional written and verbal communication abilities.
• Demonstrated ability to work independently and manage projects remotely.

• Develop and maintain key performance indicators (KPIs) and dashboards to monitor the health and efficiency of the supply chain and warehousing operations.
• Analyze vast datasets related to inventory levels, transportation costs, order fulfillment, and delivery performance to identify trends, bottlenecks, and areas for improvement.
• Design and implement predictive models for demand forecasting, inventory optimization, and network design.
• Collaborate with logistics, operations, and IT teams to define data requirements and ensure data integrity for analysis.
• Provide actionable insights and strategic recommendations to senior management regarding supply chain strategy, cost reduction initiatives, and service level improvements.
• Utilize advanced analytics and business intelligence tools (e.g., SQL, Python, R, Tableau, Power BI) to extract, manipulate, and visualize data.
• Evaluate the effectiveness of current logistics strategies and propose innovative solutions to enhance performance.
• Manage and mentor a team of supply chain analysts, fostering a culture of data-driven decision-making within a remote structure.
• Conduct scenario planning and simulation to assess the impact of potential changes to the supply chain network or operational processes.
• Stay current with emerging trends and technologies in supply chain analytics and logistics optimization.

• Bachelor's or Master's degree in Supply Chain Management, Operations Research, Statistics, Economics, or a related quantitative field.
• Minimum of 6 years of experience in supply chain analysis, logistics, or operations management, with a strong focus on data analytics.
• Proven expertise in data analysis tools and programming languages such as SQL, Python, or R.
• Proficiency with business intelligence and data visualization tools (e.g., Tableau, Power BI).
• Solid understanding of supply chain principles, including inventory management, warehousing, transportation, and demand planning.
• Experience with forecasting models and optimization techniques.
• Excellent analytical, problem-solving, and strategic thinking skills.
• Strong communication and presentation skills, with the ability to convey complex data insights to both technical and non-technical audiences.
• Demonstrated leadership and team management experience.
• Ability to thrive in a fast-paced, autonomous, and fully remote work environment.

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.