891 Statistical Software jobs in Nairobi

• Conduct original research in machine learning, deep learning, and related AI fields.
• Develop and implement novel algorithms and models for AI applications.
• Design and execute experiments to validate research hypotheses and evaluate model performance.
• Analyze large-scale datasets to extract meaningful insights and inform model development.
• Collaborate with other researchers and engineers on joint projects in a virtual setting.
• Publish research findings in leading AI conferences and journals.
• Stay abreast of the latest advancements and trends in AI and machine learning.
• Develop prototypes and proof-of-concepts for new AI technologies.
• Contribute to the strategic direction of AI research and development efforts.
• Mentor junior researchers and contribute to building a strong research culture.

• Ph.D. or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field.
• Proven track record of research publications in reputable AI conferences and journals.
• Deep expertise in machine learning algorithms, statistical modeling, and deep learning frameworks (TensorFlow, PyTorch).
• Strong programming skills, particularly in Python, with experience in relevant libraries (NumPy, SciPy, Pandas).
• Experience with big data technologies and cloud computing platforms.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills, comfortable working in a remote, distributed team.
• Ability to work independently, manage research projects, and drive innovation.

• Conduct cutting-edge research in machine learning and artificial intelligence.
• Develop and implement novel algorithms and models for AI applications.
• Design and execute experiments to validate research hypotheses and model performance.
• Analyze large datasets to extract insights and identify patterns relevant to AI research.
• Collaborate with other researchers and engineers to advance AI capabilities.
• Publish research findings in leading academic conferences and journals.
• Contribute to the development of AI-powered products and services.
• Stay abreast of the latest advancements and trends in the field of AI and machine learning.
• Mentor junior researchers and interns.
• Translate complex research concepts into practical implementations.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Proven track record of impactful research and publications in top-tier AI/ML venues.
• Minimum of 7 years of research experience in AI and machine learning.
• Expertise in one or more areas: deep learning, reinforcement learning, natural language processing, computer vision, etc.
• Proficiency in programming languages such as Python.
• Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Strong understanding of mathematical and statistical foundations of machine learning.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills for presenting research and collaborating with teams.
• Ability to work independently and manage research projects effectively in a remote setting.
• Experience with distributed computing frameworks (e.g., Spark) is a plus.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Minimum of 8 years of relevant research experience in AI/ML.
• Extensive publication record in top-tier AI/ML conferences and journals.
• Deep theoretical and practical expertise in machine learning, deep learning, and statistical modeling.
• Proficiency in programming languages such as Python and relevant ML libraries (e.g., TensorFlow, PyTorch).
• Experience with large-scale data analysis and distributed computing frameworks (e.g., Spark).
• Proven ability to lead research projects and mentor junior scientists.
• Strong problem-solving skills and creativity in developing novel AI solutions.
• Excellent communication and presentation skills.
• Experience with cloud computing platforms (AWS, GCP, Azure) is a plus.

• Conduct cutting-edge research in machine learning, deep learning, and related AI fields.
• Design, develop, and implement advanced AI algorithms and models for various applications.
• Prototype and experiment with new AI technologies, frameworks, and approaches.
• Analyze and interpret large datasets to train and validate AI models.
• Optimize model performance for scalability, efficiency, and accuracy.
• Collaborate with software engineers to integrate AI models into production systems.
• Stay abreast of the latest advancements in AI research and industry trends.
• Publish research findings in reputable conferences and journals.
• Mentor junior researchers and engineers, fostering a collaborative research environment.
• Contribute to the intellectual property strategy through invention disclosures and patent applications.
• Evaluate and select appropriate tools, libraries, and platforms for AI development.
• Ensure the ethical and responsible development and deployment of AI technologies.
• Participate in cross-functional team meetings and contribute to strategic planning.
• Develop clear and concise technical documentation for research projects and implemented solutions.
• Present research progress and findings to internal stakeholders and at external forums.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 7 years of progressive experience in AI/ML research and development.
• Proven track record of developing and deploying complex machine learning models (e.g., neural networks, NLP, computer vision).
• Expertise in programming languages such as Python, and proficiency with ML frameworks like TensorFlow, PyTorch, or Keras.
• Strong understanding of statistical modeling, data mining, and algorithm design.
• Experience with big data technologies (e.g., Spark, Hadoop) is highly desirable.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional communication and presentation skills, essential for remote collaboration and disseminating research.
• Ability to work independently, drive research initiatives, and manage projects effectively in a remote setting.
• Experience with cloud computing platforms (AWS, Azure, GCP) for ML workloads is a plus.
• Strong publication record in top-tier AI/ML venues is advantageous.

• Conduct cutting-edge research in artificial intelligence and machine learning.
• Design, develop, and implement advanced ML algorithms and models.
• Analyze large datasets and perform statistical analysis to extract insights.
• Develop and deploy machine learning models for production environments.
• Collaborate with cross-functional teams to define research problems and solutions.
• Stay abreast of the latest advancements in AI and ML research.
• Publish research findings in top-tier conferences and journals.
• Mentor junior researchers and contribute to the team's knowledge base.
• Evaluate the performance and scalability of AI models.
• Contribute to the development of AI strategy and roadmap.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 5+ years of experience in AI/ML research and development.
• Proven track record of research contributions (publications, patents).
• Expertise in one or more areas of ML: deep learning, NLP, computer vision, reinforcement learning.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong understanding of algorithms, data structures, and statistical modeling.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills for remote teamwork.
• Ability to work independently, manage projects, and drive research initiatives.

• Defining and executing a research roadmap in AI/ML.
• Leading and mentoring a team of research scientists and engineers.
• Developing novel AI algorithms and models for complex problems.
• Designing and conducting rigorous experiments to validate hypotheses.
• Analyzing large datasets to extract meaningful insights.
• Collaborating with product teams to integrate AI solutions into applications.
• Publishing research findings in leading academic conferences and journals.
• Staying abreast of the latest advancements in AI and ML research.
• Securing research grants and managing project budgets.
• Presenting research outcomes to technical and non-technical stakeholders.

• Ph.D. in Computer Science, AI, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 7 years of research experience in AI/ML, with at least 3 years in a leadership role.
• Strong publication record in top-tier AI/ML venues.
• Deep theoretical understanding of deep learning, reinforcement learning, natural language processing, computer vision, etc.
• Proficiency in programming languages such as Python, R, or C++.
• Experience with deep learning frameworks (TensorFlow, PyTorch).
• Proven ability to lead and inspire a research team.
• Excellent communication, presentation, and interpersonal skills.
• Experience with cloud computing platforms (AWS, GCP, Azure).

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.