771 Machine Learning Frameworks 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.

• Assisting in the collection, processing, and cleaning of large datasets from various sources.
• Performing exploratory data analysis (EDA) to uncover patterns and trends.
• Developing and testing predictive models using machine learning algorithms.
• Creating data visualizations to communicate findings effectively.
• Collaborating with senior data scientists on project tasks and analysis.
• Learning and applying statistical techniques and programming languages (e.g., Python, R).
• Participating in team meetings and contributing to project discussions.
• Documenting methodologies, findings, and code.
• Gaining exposure to data warehousing, big data technologies, and cloud platforms.
• Developing problem-solving skills through real-world data challenges.
• Receiving mentorship and guidance from experienced professionals.
• Contributing to the development of innovative data-driven solutions.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
• Strong analytical and problem-solving abilities.
• Familiarity with programming languages such as Python or R is a plus.
• Basic understanding of statistical concepts and machine learning principles.
• Excellent written and verbal communication skills.
• Ability to work independently and manage time effectively in a remote environment.
• Eagerness to learn and a strong work ethic.
• Ability to collaborate effectively within a remote team.
• Enthusiasm for data and its potential to drive business value.

• Assist in data collection, cleaning, and preprocessing from various sources.
• Perform exploratory data analysis to identify trends, patterns, and insights.
• Support the development and implementation of machine learning models under the guidance of senior data scientists.
• Create data visualizations and reports to communicate findings to technical and non-technical audiences.
• Contribute to the documentation of data science projects and methodologies.
• Learn and apply statistical techniques and algorithms.
• Collaborate with team members on data-related tasks and projects.
• Participate in team meetings and contribute to problem-solving discussions.
• Gain exposure to data warehousing, big data technologies, and cloud platforms.
• Stay updated on emerging trends and techniques in data science and artificial intelligence.

• Recent graduate with a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
• Solid understanding of statistical concepts and methodologies.
• Proficiency in at least one programming language commonly used in data science (e.g., Python, R).
• Familiarity with data manipulation libraries (e.g., Pandas, NumPy).
• Basic knowledge of machine learning algorithms and concepts.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills.
• Eagerness to learn and a proactive attitude.
• Ability to work independently and manage tasks effectively in a remote setting.
• Familiarity with SQL is a plus.

• Gain practical experience in data manipulation and exploratory data analysis using Python or R.
• Learn to build and evaluate machine learning models for various applications.
• Develop skills in data visualization techniques to communicate insights effectively.
• Assist senior data scientists in identifying data trends and generating actionable insights.
• Participate in team meetings, project discussions, and knowledge-sharing sessions.
• Work with real-world datasets from diverse industries.
• Understand ethical considerations and best practices in data science.
• Receive mentorship and guidance from seasoned data professionals.

• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
• Demonstrated passion for data analysis and a strong desire to learn data science.
• Basic programming skills in Python or R.
• Solid understanding of statistical concepts.
• Excellent analytical and problem-solving abilities.
• Strong communication skills, both written and verbal, for remote collaboration.
• Self-motivated and able to work independently in a remote setting.
• Eagerness to embrace new technologies and methodologies.
• Ability to commit to the full duration of the apprenticeship.