2,494 Lead Clinical Research Associate Remote jobs in Kenya

• 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.

• Develop and implement advanced analytical models to assess player performance, team strategies, and competition dynamics.
• Collect, clean, and analyze large datasets from various sports sources (e.g., performance tracking, match data).
• Create compelling visualizations and dashboards to communicate insights to coaches, athletes, and management.
• Identify key performance indicators (KPIs) and track progress towards strategic goals.
• Collaborate with stakeholders to understand their data needs and deliver tailored analytical solutions.
• Research and recommend new analytical tools and technologies to enhance capabilities.
• Provide data-driven recommendations to improve athlete training, injury prevention, and game strategies.
• Monitor industry trends in sports analytics and incorporate best practices.
• Present findings and insights to diverse audiences, including non-technical stakeholders.
• Contribute to the overall strategic planning and development of sports programs.

• Master's degree in Statistics, Data Science, Sports Science, or a related quantitative field.
• Minimum of 6 years of experience in sports analytics or a closely related field.
• Proven experience with statistical analysis, machine learning, and data mining techniques.
• Proficiency in data visualization tools (e.g., Tableau, Power BI) and programming languages (e.g., Python, R).
• Strong understanding of various sports and their performance metrics.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional communication and presentation abilities, with the capacity to explain complex data to diverse audiences.
• Experience working in a remote team environment.

• 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.

• Lead and mentor a team of sports analytics professionals.
• Develop and implement advanced statistical models and analytical frameworks for sports performance.
• Oversee data collection, cleaning, and processing for diverse sports datasets.
• Analyze performance data to identify trends, predict outcomes, and provide strategic insights.
• Collaborate with coaches, athletes, and management to define KPIs and inform decision-making.
• Develop data visualization tools and reports to effectively communicate findings.
• Research and integrate new analytical techniques and technologies.
• Present complex analytical results to non-technical audiences.
• Ensure the integrity and accuracy of all data analyses.

• Master's or Ph.D. in Statistics, Data Science, Sports Science, Mathematics, or a related quantitative field.
• 5+ years of experience in sports analytics, with proven leadership capabilities.
• Expertise in statistical modeling, machine learning, and data mining techniques.
• Proficiency in programming languages such as Python or R, and SQL.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Deep understanding of sports performance metrics and analysis.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication, presentation, and interpersonal skills.
• Ability to lead and inspire a remote team.

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.