380 Senior Data Scientist jobs in Nairobi

• 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.

• 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.

• 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.

• Assist in the collection, cleaning, and pre-processing of large datasets for AI model training.
• Support the development and implementation of machine learning models and algorithms under the guidance of senior researchers.
• Conduct exploratory data analysis to identify patterns and insights relevant to research objectives.
• Help in the evaluation and validation of model performance using various metrics.
• Contribute to the documentation of research findings, methodologies, and code.
• Participate in team meetings and brainstorming sessions to discuss project progress and future directions.
• Research and present relevant academic papers and industry trends in AI and ML.
• Assist in the preparation of research reports and presentations for internal and external audiences.
• Implement and test new AI techniques and frameworks.
• Collaborate with other interns and team members on assigned tasks.
• Ensure code is well-documented and follows best practices for reproducibility.
• Learn and apply advanced statistical and computational techniques relevant to AI research.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, or a related quantitative field.
• Solid understanding of fundamental machine learning concepts and algorithms.
• Proficiency in Python and experience with relevant libraries such as TensorFlow, PyTorch, scikit-learn, pandas, and NumPy.
• Familiarity with data manipulation and analysis techniques.
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills, both written and verbal, with the ability to articulate technical concepts clearly.
• Ability to work effectively in a remote, collaborative team environment.
• Eagerness to learn and adapt to new technologies and research challenges.
• Previous exposure to AI research projects or Kaggle competitions is a plus.
• Demonstrated passion for artificial intelligence and its applications.

A Business Data Analytics and Research intern plays a crucial role in organizations by leveraging data to drive strategic decision-making, conducting research to identify market trends, and optimizing business operations. Below are key responsibilities and skills typically associated with this role:

Key Responsibilities:

1. Data Collection and Analysis
   :

2. Gather and analyze business, market, and financial data from various sources to provide insights into performance and trends.

3. Use statistical tools to interpret data sets, identifying patterns and trends that inform business decisions.

2.Data Visualization, Reporting and Presentation
:

• Prepare and present detailed reports, dashboards, and visualizations that summarize key data insights and findings.
• Communicate complex data results to non-technical stakeholders in a clear and actionable manner.
• Capacity to develop concept notes and proposals based on market research gaps

3. Market Research
:

• Conduct qualitative and quantitative research to identify new market opportunities, competitor analysis, and customer preferences.
• Evaluate market conditions, industry trends, and competitors' activities to support business growth strategies.
• Prepare presentations based on market research reports

4.Business Performance Monitoring
:

• Monitor key performance indicators (KPIs) to track business progress and identify areas for improvement.
• Recommend improvements based on data insights to optimize processes, reduce costs, and increase profitability.

5.Collaborating with Teams
:

• Work closely with different departments such as marketing, finance, and operations to align data-driven insights with business objectives.
• Provide support for product development, sales strategies, and customer experience initiatives through data analysis.

6.Data Management
:

• Ensure the accuracy, completeness, and security of data.
• Develop and maintain databases, data collection systems, and strategies for efficient data storage and retrieval.

Key Skills:

1.Data Analytics Tools
:

• Proficient in tools like SQL, Excel, Tableau, Power BI, Google Analytics, and other business intelligence platforms.

2.Statistical Analysis
:

• Knowledge of statistical software (e.g., R, SAS, SPSS) and techniques such as regression analysis, hypothesis testing, and predictive modeling.

3.Research and Excellent Writing skills:

• Strong ability to conduct both primary and secondary research, including surveys, interviews, and literature reviews.
• Capacity to develop report and concepts based on market research reports

4.Problem-Solving
:

• Analytical thinking to identify issues, trends, and opportunities through data, and propose actionable solutions.

5.Communication Skills
:

• Excellent written and verbal communication skills to present findings and recommendations clearly to stakeholders.

6.Attention to Detail
:

• High level of precision in handling large data sets and ensuring data accuracy.

7.Project Management
:

• Ability to manage multiple research projects simultaneously, ensuring timely delivery of results.

Education, knowledge and experience:

• A degree in Agricultural Economics or a related field.
• Experience in management and analysis of data.
• Field experience and synthesis of data and lessons for learning
• Knowledge and savvy of data analysis software, especially Stata.
• Very strong analytical skills and applied statistical experience.
• Good scientific wring experience.