549 Data Science 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.

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 from various sources.
• Apply statistical methods and machine learning algorithms to analyze data and build predictive models.
• Develop and implement data visualization techniques to communicate findings effectively.
• Collaborate with senior data scientists on project design and execution.
• Document methodologies, code, and results thoroughly.
• Participate in team meetings and contribute to discussions on data-driven strategies.
• Support the development of dashboards and reports for stakeholders.
• Conduct literature reviews on relevant data science topics.

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Foundational knowledge of statistical concepts and machine learning algorithms.
• Proficiency in at least one programming language commonly used in data science (e.g., Python, R).
• Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Basic understanding of data visualization tools (e.g., Matplotlib, Seaborn).
• Strong analytical and critical thinking skills.
• Excellent communication and collaboration skills, especially in a virtual setting.
• A proactive attitude and a strong desire to learn and grow in the field of data science.

• Assist in the collection, cleaning, and preparation of large datasets.
• Perform exploratory data analysis to identify trends and patterns.
• Support the development and implementation of machine learning models.
• Create data visualizations and reports to communicate findings.
• Collaborate with senior data scientists and cross-functional teams on projects.
• Participate in training sessions and knowledge-sharing activities.
• Document data analysis processes and model methodologies.
• Assist in testing and validating data science solutions.
• Stay updated on emerging trends and techniques in data science and AI.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Strong understanding of statistical concepts and analytical techniques.
• Proficiency in at least one programming language commonly used in data science (e.g., Python, R).
• Familiarity with data manipulation libraries (e.g., Pandas) and data visualization tools.
• Excellent problem-solving skills and attention to detail.
• Strong communication and teamwork abilities.
• Eagerness to learn and adapt in a fast-paced, remote environment.
• A genuine passion for data and its potential to drive business value.

• Assist in data collection, cleaning, and preprocessing activities.
• Support the development and testing of machine learning models.
• Perform exploratory data analysis and generate visualizations.
• Contribute to data-driven insights and reporting.
• Learn and apply statistical techniques and data mining methods.
• Collaborate with senior data scientists on ongoing projects.
• Participate actively in training sessions and team meetings.
• Assist in documentation of data science processes and methodologies.

• Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience.
• Basic understanding of programming languages like Python or R.
• Familiarity with data analysis and visualization concepts.
• Strong analytical and problem-solving aptitude.
• Eagerness to learn and develop skills in data science and machine learning.
• Good communication and interpersonal skills for remote collaboration.
• Ability to work independently and manage learning tasks.