1,054 AI Researchers jobs in Kenya

• Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Foundational knowledge of programming languages such as Python or R.
• Basic understanding of statistical concepts and machine learning principles.
• Familiarity with data manipulation and analysis tools (e.g., SQL, Pandas).
• Strong analytical and problem-solving abilities.
• Excellent written and verbal communication skills.
• Ability to work independently and manage tasks effectively in a remote setting.
• Eagerness to learn and adapt to new technologies and methodologies.
• A genuine interest in data and its applications.

• Data Preprocessing and Exploration
• Feature Engineering and Selection
• Supervised and Unsupervised Machine Learning Algorithms (e.g., Regression, Classification, Clustering)
• Model Evaluation and Tuning
• Introduction to Deep Learning Concepts
• Data Visualization and Storytelling
• Programming with Python (libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
• Big Data Technologies (exposure to platforms like Spark)
• Version Control (Git) and Collaboration Tools
• Best practices for remote collaboration and communication in a tech environment.

• Strong analytical and quantitative skills.
• Proficiency in at least one programming language, preferably Python.
• Understanding of basic statistics and calculus.
• A keen interest in data science, machine learning, and artificial intelligence.
• Excellent problem-solving skills and attention to detail.
• Ability to work independently and manage time effectively in a remote setting.
• Good communication skills, with the ability to explain technical concepts to a non-technical audience.
• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) or equivalent practical experience.
• Must be eligible to work remotely from Kenya.

You are applying to be part of the Novartis Talent Pool. We are not currently recruiting for this role, but we are building a pipeline for future opportunities. If you would like to be considered for a similar position in the future, then please submit your CV.
Key Responsibilities

• Drive innovation using data science, AI, and effective data management to solve complex business challenges
• Translate analytical findings into clear, actionable recommendations for non-technical stakeholders
• Develop and implement pathways for effective data use across analytical functions
• Present insights through smart visualization and storytelling to influence strategic decisions
• Allocate team resources efficiently, manage change, and resolve operational risks proactively
• Collaborate with internal teams, external partners, and institutions to deliver impactful solutions
• Evaluate and adopt new technologies and tools to enhance data science practices and efficiency

Essential Requirements

• Minimum of 5 years of experience in data science, with a strong record of applied analytics
• Proven expertise in Python and R programming for statistical analysis and machine learning
• Deep understanding of data governance, data quality, and master data management principles
• Experience with big data technologies and platforms, including Apache Spark
• Strong communication skills to present complex insights to non-technical stakeholders
• Fluent in English, with the ability to collaborate across global, cross-functional teams

Desirable Requirements

• Experience publishing in peer-reviewed journals or presenting at professional conferences
• Familiarity with cross-industry collaboration and external working groups

Commitment to Diversity and Inclusion / EEO:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Primary Location: Prague, CZ

Other Locations: Barcelona, Spain

Relocation Support: This role is based in Prague, CZ. Novartis is unable to offer relocation support: please only apply if accessible.

• Assist in collecting, cleaning, and pre-processing large datasets.
• Perform exploratory data analysis to identify trends and patterns.
• Support the development and testing of machine learning models.
• Create data visualizations to communicate findings effectively.
• Collaborate with senior team members on data-driven projects.
• Contribute to documentation of data processes and methodologies.
• Participate in team meetings and present findings in a clear, concise manner.
• Learn and apply new data analysis techniques and tools.
• Assist in generating reports and dashboards.

• Recent graduate with a degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong understanding of statistical concepts and methods.
• Proficiency in at least one programming language such as Python or R.
• Familiarity with data manipulation libraries (e.g., Pandas, dplyr).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, ggplot2).
• Excellent analytical and problem-solving skills.
• Strong communication skills, both written and verbal, for remote collaboration.
• Ability to work independently and manage time effectively in a remote setting.
• Eagerness to learn and adapt to new technologies and methodologies.

• Assist in cleaning, transforming, and preparing datasets for analysis.
• Perform exploratory data analysis (EDA) to uncover patterns and insights.
• Support the development and implementation of data models.
• Learn and apply statistical techniques and machine learning algorithms.
• Contribute to data visualization and reporting efforts.
• Participate in team meetings and contribute to project discussions.
• Document methodologies and findings accurately.
• Develop proficiency in data science tools and programming languages.
• Collaborate effectively with senior data scientists in a remote team environment.

• Currently pursuing or recently completed a degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Basic understanding of statistical concepts and principles.
• Familiarity with at least one programming language (e.g., Python, R) is a plus.
• Strong analytical and problem-solving skills.
• Eagerness to learn and adapt to new technologies and methodologies.
• Excellent organizational and time management skills for remote work.
• Good communication skills, both written and verbal.
• Ability to work independently and as part of a virtual team.
• A genuine passion for data and its applications.

• Assist senior data scientists in collecting, cleaning, and pre-processing large datasets from various sources.
• Learn and apply statistical analysis techniques to identify patterns, trends, and insights within the data.
• Support the development and implementation of machine learning models under the guidance of experienced mentors.
• Contribute to the creation of data visualizations and reports to communicate findings to stakeholders.
• Participate in code reviews and collaborate with team members to ensure code quality and efficiency.
• Gain hands-on experience with data analysis tools and programming languages such as Python and R.
• Learn about different machine learning algorithms and their applications.
• Assist in the documentation of data science processes, methodologies, and results.
• Engage in continuous learning and stay updated with the latest advancements in data science and artificial intelligence.
• Troubleshoot and resolve data-related issues as they arise.
• Help in the design and execution of experiments to test hypotheses.
• Develop a strong understanding of data ethics and best practices.

• A strong passion for data science, mathematics, statistics, and computer science.
• A Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Economics, or a related discipline.
• Basic understanding of programming concepts, preferably with exposure to Python or R.
• Strong analytical and problem-solving skills.
• Excellent communication skills, both written and verbal, with the ability to explain complex ideas simply.
• A proactive learner with a strong desire to acquire new skills and knowledge.
• Ability to work independently and collaboratively in a remote team environment.
• High level of attention to detail and accuracy.
• Enthusiasm for working with data and uncovering insights.
• Previous exposure to data analysis projects (academic or personal) is a plus.

• Work on challenging data science projects using real datasets.
• Gain practical experience with programming languages like Python and R, and relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Learn about data cleaning, feature engineering, model building, and evaluation.
• Develop skills in data visualization tools and techniques to communicate insights effectively.
• Receive mentorship and guidance from senior data scientists throughout the program.
• Participate in training sessions and workshops focused on data science methodologies and tools.
• Contribute to team discussions, problem-solving, and innovative solutions.
• Develop a strong understanding of business applications of data science.
• Network with professionals across various departments within the organization.
• Receive a certificate of completion upon successful program fulfillment.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a closely related quantitative field.
• Strong analytical and problem-solving skills.
• Foundational knowledge of statistical concepts and machine learning algorithms.
• Familiarity with programming languages such as Python or R is essential.
• Excellent communication and interpersonal skills, with the ability to explain technical concepts clearly.
• Proactive, self-motivated, and eager to learn new technologies and methodologies.
• Ability to work effectively independently in a remote setting and as part of a collaborative team.
• High attention to detail and commitment to producing high-quality work.
• A genuine passion for data and its potential to drive business value.