949 Remote Aviation Performance Analyst jobs in Kenya

• Collect, clean, and analyze diverse aviation operational data.
• Develop and maintain performance metrics and dashboards.
• Identify trends, anomalies, and areas for operational improvement.
• Perform statistical analysis of flight performance, fuel efficiency, and network operations.
• Prepare comprehensive reports and present findings to stakeholders.
• Collaborate with operational teams to implement performance enhancements.
• Utilize data visualization tools to communicate insights effectively.
• Stay abreast of industry best practices in aviation performance analysis.
• Contribute to strategic planning through data-driven recommendations.
• Ensure data accuracy and integrity throughout the analysis process.

• Bachelor's degree in Aviation Management, Statistics, Data Science, Engineering, or a related field.
• Minimum of 4 years of experience in aviation performance analysis or a similar analytical role.
• Proficiency in data analysis software (e.g., Python, R, SQL) and statistical methods.
• Experience with aviation-specific data and operational metrics.
• Strong understanding of flight operations, fuel management, and network planning.
• Excellent analytical, problem-solving, and critical thinking skills.
• Superior communication and presentation abilities.
• Ability to work independently and manage time effectively in a remote setting.
• Familiarity with BI tools (e.g., Tableau, Power BI) is a plus.

• Collect, clean, and analyze sports performance data from various sources (e.g., statistical databases, video analysis, wearable devices).
• Develop and implement advanced analytical models to assess player and team performance.
• Identify key performance indicators (KPIs) and provide data-driven insights to coaches and athletes.
• Create compelling data visualizations and reports to communicate findings effectively.
• Collaborate with coaching staff to develop personalized training plans and game strategies.
• Research and evaluate new technologies and methodologies for sports analytics.
• Stay up-to-date with the latest trends and innovations in sports science and analytics.
• Contribute to the development of predictive models for player performance and game outcomes.
• Assist in scouting and talent identification processes through data analysis.
• Maintain data integrity and ensure the security of sensitive performance information.

• Master's degree in Sports Science, Data Science, Statistics, Computer Science, or a related quantitative field.
• Minimum of 5 years of experience in sports analytics, performance analysis, or a related role.
• Proven experience in collecting, analyzing, and interpreting sports performance data.
• Strong knowledge of statistical modeling, data mining, and machine learning techniques.
• Proficiency in programming languages such as Python or R, and experience with data visualization tools (e.g., Tableau, Power BI).
• Familiarity with sports-specific data platforms and video analysis software.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong written and verbal communication skills, crucial for effective remote collaboration.
• Ability to work independently, manage multiple projects, and meet deadlines in a fast-paced remote environment.
• A deep passion for sports and a strong understanding of athletic performance principles.
• Experience in (mention a specific sport, e.g., football, basketball, athletics) is highly valued.

Job Summary

We are seeking a highly skilled Data Analyst with a strong focus on financial modeling. In this role, financial modeling is the core responsibility—you will spend most of your time building and refining models that drive strategic client decisions. Data skills (SQL, Python, BigQuery) will enable you to scale and optimize that work.

This role is client-facing: you'll collaborate directly with CFOs and other analysts to deliver outputs seen by clients. Accuracy, clarity, and attention to detail are critical, as mistakes can directly impact client trust. The ideal candidate is passionate about financial modeling, eager to learn across industries, and thrives in a collaborative, fast-changing environment.

Key Responsibilities

1. Financial Modeling (Core)

o Build, refine, and maintain cash flow forecasts, KPI analytics, and operating financial models.

o Ensure models are modular, intuitive, and user-friendly, enabling broad usability across multiple clients.

o Translate P&L statements, KPIs, and financial data into actionable forecasts and insights.

2. Client-Facing Analysis

o Deliver financial insights directly to clients with clarity and professionalism.

o Collaborate with CFOs and analysts to provide strategic recommendations.

o Adapt quickly to different industries and business models—no two clients are alike.

3. Data Analysis & Reporting

o Use SQL (preferably Google BigQuery) to collect and analyze datasets.

o Apply Python for advanced data processing, automation, and visualization.

o Support the design of scalable systems for financial data and KPI analysis.

4. Collaboration & Problem-Solving

o Work closely with cross-functional teams in a highly collaborative environment.

o Contribute to new approaches, dashboards, and tools that push the boundaries of how CFOs operate.

o Approach challenges with creativity, intellectual sharpness, and entrepreneurial spirit.

Required Qualifications

· Bachelor's degree from a top-tier university in Data Analytics, Finance, Computer Science, Engineering or a related field.

· Proven expertise in financial modeling (cash flow forecasting, KPI analytics, operating models).

· Proficiency in SQL and Python.

· Strong financial acumen and understanding of operating-level finance.

· Excellent analytical and problem-solving skills with attention to detail.

Preferred Qualifications

· Experience with Google BigQuery or similar cloud SQL environments.

· Familiarity with data pipelines, ETL processes, or scalable data workflows.

· Exposure to cloud platforms such as GCP.

· Advanced Excel/Google Sheets skills for financial modeling.

· Experience with B2C (consumer product) companies.

· Familiarity with BI/analytics tools such as Looker, Tableau, or dbt (helpful, not required).

Soft Skills

· Passion for financial modeling—comfortable working on it daily.

· High accountability: understands the sensitivity of client-facing work.

· Strong communication skills to explain complex insights clearly.

· Ability to learn quickly and adapt to changing client needs.

· Entrepreneurial mindset with curiosity and creativity.

What You'll Gain

· Exposure to a wide range of clients, industries, and metrics.

· The opportunity to build financial products and models that shape CFO functions across companies.

· A collaborative environment where sharp thinkers and problem-solvers thrive.

• Collect, clean, and process large sports-related datasets.
• Develop and apply statistical models to analyze player and team performance.
• Create predictive models for game outcomes, player development, and strategic planning.
• Visualize data and present findings through reports, dashboards, and presentations.
• Collaborate with coaches, athletes, and management to provide data-driven insights.
• Identify trends and patterns in sports data to inform decision-making.
• Stay updated on the latest advancements in sports analytics techniques and technologies.
• Ensure data integrity and accuracy throughout the analysis process.
• Contribute to the development of new analytical tools and methodologies.
• Communicate complex analytical concepts to diverse audiences.

• Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field. A Master's degree is preferred.
• Minimum of 3 years of experience in data analysis, statistical modeling, or a similar role, preferably within the sports industry.
• Proficiency in programming languages such as Python or R.
• Strong knowledge of SQL and database management.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Solid understanding of statistical concepts and machine learning techniques.
• Deep knowledge and passion for one or more sports.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation abilities.
• Ability to work independently and manage projects in a remote environment.

• Develop and implement sophisticated statistical models and machine learning algorithms to analyze sports performance data.
• Collect, clean, and process large datasets from various sources, including performance tracking, video analysis, and biometric sensors.
• Identify key performance indicators (KPIs) and develop dashboards to visualize trends and insights for coaches, athletes, and management.
• Provide objective, data-backed recommendations to improve player development, training regimens, and tactical decision-making.
• Conduct in-depth analysis of opponent strategies and identify competitive advantages.
• Collaborate closely with coaching staff and athletes to understand their needs and deliver tailored analytical support.
• Stay current with the latest trends and technologies in sports analytics and data science.
• Communicate complex analytical findings clearly and concisely to both technical and non-technical stakeholders.
• Mentor and guide junior analysts, fostering a culture of continuous learning and improvement.
• Manage the deployment and maintenance of analytics platforms and tools.
• Ensure data integrity and privacy across all analytical processes.

• Master's degree or PhD in Statistics, Data Science, Sports Science, Mathematics, or a related quantitative field.
• At least 5 years of professional experience in sports analytics or a closely related field.
• Proven expertise in statistical modeling, machine learning, and data mining techniques.
• Proficiency in programming languages such as Python or R and associated data science libraries (e.g., Pandas, NumPy, Scikit-learn).
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Deep understanding of various sports and their performance metrics.
• Excellent problem-solving and critical thinking abilities.
• Strong presentation and communication skills, with the ability to translate complex data into understandable insights.
• Demonstrated ability to work independently and collaboratively in a remote setting.
• Experience with SQL and database management.
• Knowledge of sports performance tracking systems is a plus.

• Design, develop, and implement advanced statistical models and machine learning algorithms to analyze player performance, team dynamics, and game outcomes across multiple sports.
• Extract, clean, and process large datasets from diverse sources, ensuring data integrity and accuracy.
• Develop and maintain comprehensive performance dashboards and reports for clients, translating complex analytical findings into clear, concise, and visually appealing presentations.
• Collaborate with sports coaches, performance analysts, and management to understand their specific analytical needs and provide tailored data-driven solutions.
• Stay abreast of the latest research and technological advancements in sports analytics, data science, and machine learning, and apply them to enhance existing methodologies and develop new analytical capabilities.
• Contribute to the development of proprietary analytical tools and software solutions.
• Mentor junior analysts and provide guidance on analytical best practices.
• Participate in client meetings and present findings and recommendations.
• Ensure compliance with data privacy regulations and ethical data handling practices.

• Master's or Ph.D. in Statistics, Data Science, Computer Science, Sports Science, Mathematics, or a related quantitative field.
• Minimum of 5 years of professional experience in sports analytics or a closely related field, with a proven track record of delivering impactful insights.
• Strong proficiency in programming languages such as Python or R, and experience with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Expertise in database querying languages (e.g., SQL) and experience working with large, complex datasets.
• In-depth knowledge of statistical modeling techniques, machine learning algorithms, and experimental design.
• Familiarity with major sports leagues and their data structures is highly desirable.
• Excellent communication, presentation, and interpersonal skills, with the ability to explain technical concepts to non-technical audiences.
• Proven ability to work independently and manage multiple projects simultaneously in a remote work environment.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib) is a plus.

• Collect, clean, and analyze large datasets related to sports performance, including player statistics, game events, and biomechanical data.
• Develop and implement statistical models to identify key performance indicators and predict outcomes.
• Create compelling visualizations and dashboards to communicate analytical insights effectively.
• Collaborate with coaches, athletes, and management to understand their data needs and provide tailored insights.
• Identify opportunities to improve team strategy, player development, and operational efficiency through data analysis.
• Research and stay updated on the latest trends and technologies in sports analytics and data science.
• Contribute to the development of data-driven decision-making processes within the organization.
• Design and evaluate experiments to test hypotheses related to performance and strategy.
• Maintain data integrity and ensure the security of sensitive information.
• Prepare reports and presentations summarizing findings and recommendations.

• Bachelor's degree in Statistics, Data Science, Mathematics, Sports Science, or a related quantitative field. A Master's degree is preferred.
• Minimum of 3 years of experience in sports analytics or a related data analysis role.
• Proficiency in statistical programming languages such as Python (with libraries like Pandas, NumPy, Scikit-learn) or R.
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.
• Strong understanding of statistical concepts, modeling techniques, and experimental design.
• A passion for sports and a solid understanding of various sports and their performance metrics.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Ability to work independently and manage multiple projects in a remote setting.
• Experience with sports-specific analytics platforms or databases is a plus.

• 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.