2,279 Predictive Models jobs in Kenya

• Design, develop, and implement advanced machine learning models for predictive analytics, forecasting, and anomaly detection.
• Collaborate with stakeholders across various departments to identify business challenges and opportunities for data science solutions.
• Perform data exploration, cleaning, and feature engineering on large, complex datasets.
• Select appropriate algorithms and statistical methods to address specific research questions and business objectives.
• Validate model performance, interpret results, and communicate findings effectively to both technical and non-technical audiences.
• Develop and maintain robust data pipelines for model training and deployment.
• Stay abreast of the latest research and advancements in data science, machine learning, and artificial intelligence.
• Contribute to the development of scalable data science infrastructure and tools.
• Mentor junior data scientists and contribute to the growth of the data science community within the organization.
• Document methodologies, code, and results thoroughly.
• Present research findings and recommendations to senior leadership and cross-functional teams.
• Identify new data sources and methodologies to enhance predictive capabilities.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Minimum of 5 years of experience in data science, with a strong focus on predictive modeling and machine learning.
• Proficiency in programming languages such as Python or R, and relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy).
• Extensive experience with statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and validation techniques.
• Experience working with large datasets and distributed computing frameworks (e.g., Spark) is desirable.
• Strong understanding of data structures, algorithms, and software development best practices.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex concepts clearly.
• Ability to work independently and collaboratively in a remote research environment.
• Experience with cloud platforms (AWS, Azure, GCP) is a plus.

• Design, develop, and implement state-of-the-art machine learning models and algorithms for predictive analytics.
• Build and maintain scalable ML pipelines for data ingestion, feature engineering, model training, and deployment.
• Conduct rigorous experimentation and validation of models to ensure accuracy, robustness, and performance.
• Collaborate with data scientists and software engineers to integrate ML models into production systems.
• Research and apply new AI/ML techniques and technologies to solve complex business problems.
• Optimize existing models for improved efficiency, speed, and resource utilization.
• Develop and maintain comprehensive documentation for ML models and processes.
• Stay abreast of the latest advancements in AI, machine learning, and deep learning research.
• Mentor junior engineers and contribute to the team's knowledge sharing and technical growth.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Statistics, Mathematics, or a related quantitative field.
• 5+ years of hands-on experience in developing and deploying machine learning models in production environments.
• Proficiency in Python and common ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of algorithms, data structures, and statistical modeling.
• Experience with cloud platforms (AWS, Azure, GCP) and ML services.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills, with the ability to work effectively in a remote team.
• Published research or contributions to open-source ML projects are highly desirable.
• This position is 100% remote, offering a unique opportunity to work on groundbreaking AI projects without geographical constraints.

• Design, develop, and implement machine learning models and algorithms.
• Perform data mining, feature engineering, and data preprocessing for model training.
• Evaluate and optimize model performance using various metrics.
• Deploy machine learning models into production environments.
• Collaborate with data scientists and software engineers to integrate AI solutions.
• Conduct research on state-of-the-art AI/ML techniques and algorithms.
• Build and maintain data pipelines for ML workflows.
• Troubleshoot and debug model performance issues.
• Develop and maintain documentation for AI/ML projects.
• Stay current with advancements in AI, machine learning, and deep learning.
• Contribute to the company's intellectual property through innovation.
• Present technical findings and insights to cross-functional teams.

• Master's degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
• 5+ years of hands-on experience in developing and deploying machine learning models.
• Proficiency in programming languages such as Python or R.
• Experience with ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of statistical modeling, algorithms, and data structures.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities in a remote setting.
• Ability to work independently and manage complex projects.
• Experience with big data technologies (e.g., Spark) is beneficial.

• Assist in the collection, cleaning, and preprocessing of diverse datasets from various sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Develop and implement basic machine learning models under the guidance of senior team members.
• Visualize data and model results using tools such as Python libraries (Matplotlib, Seaborn) or Tableau.
• Collaborate with data scientists and engineers on feature engineering and model selection.
• Document methodologies, findings, and code for reproducibility and knowledge sharing.
• Participate in regular team meetings and contribute to project discussions.
• Learn and apply new data analysis techniques and tools relevant to AI/ML.
• Assist in the testing and validation of AI/ML models.
• Contribute to the overall data strategy and innovation efforts.

• Recent graduate with a Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field.
• Foundational understanding of statistical concepts and data analysis techniques.
• Basic programming skills in Python or R, including experience with relevant data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Familiarity with machine learning concepts and algorithms is highly desirable.
• Exposure to data visualization tools.
• Strong analytical and problem-solving abilities.
• Excellent communication and teamwork skills, essential for remote collaboration.
• Proactive attitude and eagerness to learn and take on new challenges.
• Self-motivated and able to manage tasks effectively in a remote environment.
• A genuine interest in AI and Machine Learning.

• Assist in the collection, cleaning, and preprocessing of large datasets from various sources.
• Perform exploratory data analysis to identify trends, patterns, and anomalies.
• Support the development and implementation of machine learning models under the guidance of senior team members.
• Conduct literature reviews on relevant machine learning techniques and algorithms.
• Assist in the evaluation and validation of model performance.
• Develop data visualizations and reports to communicate findings to the team.
• Collaborate with team members on data-related tasks and projects.
• Learn and apply statistical methods and machine learning algorithms.
• Participate in team meetings and contribute to discussions on project progress and strategy.
• Gain practical experience with programming languages like Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).

• Recent graduate with a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Strong foundation in statistical concepts and data analysis principles.
• Basic understanding of machine learning concepts and algorithms.
• Proficiency in at least one programming language, preferably Python.
• Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Excellent analytical and problem-solving skills.
• Strong attention to detail and accuracy.
• Good communication and interpersonal skills, with the ability to work effectively in a remote team environment.
• Eagerness to learn and adapt to new technologies and methodologies.
• A genuine interest in data science, machine learning, and artificial intelligence.

• Assist in the collection, cleaning, and preprocessing of large datasets for analysis.
• Support the development and implementation of machine learning models under the guidance of senior staff.
• Perform exploratory data analysis to identify patterns, trends, and anomalies.
• Create data visualizations and reports to communicate findings effectively.
• Conduct statistical analysis and hypothesis testing.
• Collaborate with the data science team on various research and development projects.
• Document methodologies, code, and results clearly and concisely.
• Assist in the evaluation and validation of model performance.
• Learn and apply new data analysis techniques and tools.
• Participate in team meetings and contribute to project discussions.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Strong foundation in statistical concepts and analytical techniques.
• Basic understanding of machine learning algorithms and principles.
• Proficiency in at least one programming language commonly used in data analysis (e.g., Python, R).
• Familiarity with data manipulation libraries (e.g., Pandas, NumPy).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) is a plus.
• Excellent problem-solving and critical-thinking abilities.
• Strong attention to detail and accuracy.
• Good communication and teamwork skills, essential for remote collaboration.
• Enthusiasm for learning and a proactive attitude.

• Assist in collecting, cleaning, and organizing large datasets from various sources.
• Perform basic data analysis and generate reports under the guidance of senior analysts.
• Develop and maintain data visualizations to help communicate insights effectively.
• Support the development of dashboards and reports using business intelligence tools.
• Conduct research on industry trends and competitive landscape to inform analytical projects.
• Collaborate with team members on ad-hoc data analysis requests.
• Learn and apply statistical methods and data modeling techniques.
• Participate in team meetings and contribute ideas for data-driven solutions.
• Assist in documenting data sources, methodologies, and findings.
• Gain exposure to programming languages commonly used in data analysis, such as Python or R.

• Recent graduate with a Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, Data Science, or a related discipline.
• Strong analytical and problem-solving skills.
• Proficiency in Microsoft Excel for data manipulation and analysis.
• Basic understanding of statistical concepts and data analysis principles.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• Exposure to programming languages like Python or R is highly desirable.
• Excellent written and verbal communication skills.
• Ability to work independently and manage tasks effectively in a remote setting.
• Eagerness to learn and a strong work ethic.
• Enthusiasm for data and analytics.

About the Role:

Help shape the future of AI We're seeking detail-oriented freelancers to join a global AI data annotation project. As an AI Data Annotation Specialist, you'll annotate, label, and curate data that powers advanced machine learning models. Your work—tagging images, labeling text, or collecting documents—will directly impact the accuracy and performance of AI systems used worldwide.

Key Responsibilities:

• Annotate & Label: Tag, categorize, and review text, images, and documents.
• Collect Data: Gather and organize high-quality datasets for AI training.
• Ensure Quality: Review and validate data for precision and consistency.
• Collaborate Globally: Work with an international team to hit project milestones.

Basic Requirements:

• Strong attention to detail and ability to follow precise instructions.
• Reliable internet connection and ability to work independently.
• Prior experience in data annotation or labeling is a plus but not required.
• Basic understanding of AI or machine learning concepts is advantageous.
• Strong proficiency in English for clear communication and reporting.