3,107 Principal AI Research Scientist Remote jobs in Kenya

• Collect, clean, and pre-process large scientific datasets from various experimental sources.
• Perform statistical analysis on research data to identify trends, patterns, and significant findings.
• Develop and implement data visualization techniques to effectively communicate research results.
• Collaborate with researchers to define data analysis requirements and methodologies.
• Interpret complex scientific data and provide actionable insights to research teams.
• Design and execute experiments for data validation and quality control.
• Utilize statistical software and programming languages (e.g., R, Python, SPSS) for data manipulation and analysis.
• Contribute to the writing of scientific reports, publications, and presentations.
• Maintain accurate and organized documentation of data analysis processes and results.
• Stay updated with the latest advancements in data analysis techniques and relevant scientific fields.
• Contribute to the development of predictive models and analytical frameworks.
• Ensure data integrity and adherence to research ethics and protocols.

• Master's or PhD in a quantitative field such as Statistics, Mathematics, Physics, Biology, Computer Science, or a related scientific discipline.
• Proven experience in analyzing complex scientific datasets.
• Strong proficiency in statistical analysis methods and software (e.g., R, Python with libraries like Pandas, NumPy, SciPy, SPSS, SAS).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Familiarity with database management and SQL.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Ability to work independently and manage time effectively in a remote setting.
• Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences.
• Experience with scientific research methodologies.
• A proactive approach to data challenges and a commitment to scientific rigor.

• Perform in-depth analysis of large genomic datasets, including next-generation sequencing (NGS) data (e.g., WGS, WES, RNA-seq).
• Develop, implement, and validate bioinformatics pipelines for data processing, variant calling, and functional annotation.
• Apply statistical methods and machine learning techniques to identify patterns, biomarkers, and genetic associations.
• Collaborate closely with biologists, geneticists, and other researchers to design experiments and interpret results.
• Visualize complex data to effectively communicate findings to both technical and non-technical audiences.
• Contribute to the development of new analytical methodologies and computational tools.
• Maintain comprehensive documentation of analytical workflows, code, and results.
• Stay abreast of the latest advancements in genomics, bioinformatics, and computational biology.
• Mentor junior data analysts and contribute to team knowledge sharing.
• Ensure data integrity and reproducibility of analyses.

• Ph.D. or M.Sc. in Bioinformatics, Computational Biology, Statistics, Genetics, or a related quantitative field.
• 5+ years of hands-on experience in analyzing genomic data using computational tools and programming languages (e.g., Python, R, Perl).
• Proficiency with common bioinformatics software and databases (e.g., GATK, ANNOVAR, Ensembl, UCSC Genome Browser).
• Strong understanding of statistical principles and machine learning algorithms relevant to biological data.
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) is a plus.
• Excellent problem-solving skills and the ability to tackle complex analytical challenges.
• Strong written and verbal communication skills for effective collaboration in a remote team.
• Proven ability to work independently and manage multiple projects simultaneously.
• Experience in drug discovery, clinical genomics, or population genetics is highly desirable.
• Demonstrated ability to present complex scientific information clearly and concisely.
• A strong track record of contributing to scientific publications or presentations.
• This fully remote role offers the opportunity to significantly impact biological research from your home environment. You will be part of a collaborative and intellectually stimulating team, working on projects that have the potential to advance human health. Our client is committed to fostering a supportive remote work culture that encourages innovation and scientific excellence. The advanced analytical tasks and the collaborative nature of the work ensure continuous learning and professional growth. Your expertise in genomics and data analysis will be highly valued and contribute directly to the company's R&D objectives. We are looking for passionate individuals who are driven by scientific curiosity and possess the technical skills to unravel the complexities of the genome.

Summary
The Senior Research Analyst is responsible for internal project management and report writing. This role requires the ability to effectively communicate with stakeholders, manage multiple projects and analyze complex data sets, synthesize information, and present findings in a clear and concise manner. To be successful in this role, you must have strong communication skills, excellent analytical skills, attention to detail, and the ability to multitask.

Responsibilities
Participate in client meetings to ensure comprehension of client needs.

Support in writing RFPs, questionnaire design, writing research reports, strategic recommendations and client presentation.

Create statistical analysis and reporting plans, conducting analysis of results.

Full cycle project management in collaboration with the operations team to ensure quality control and adherence to project timelines, such as validating the questionnaire's test link, interviewer training, coordinating field implementation, follow-up and validation of the pre-test, daily project field monitoring, project follow-up and coordinating end of fieldwork stages.

Qualifications
Bachelor's or Master's in Sociology, Psychology, Business or related field

Minimum 4 years' work experience in client facing/customer service roles

Minimum with 2 years' Market Research experience as a Market Research Analyst, preferably on supplier side research.

Skills
Strong Project Management skill: Adept managing multiple projects and timelines at once.

Strong Client Management skill: Adept at nurturing client relationships, understanding client needs and helping clients in solving their business problems with research.

Excellent communication and presentation skills: Ability to convey complex data and insights in a clear and compelling manner.

Excellent analytical skills: Ability to examine and interpret data with keen attention to detail; identify trends, patterns, and insights, and draw meaningful conclusions that is useful for decision-making.

• Lead cutting-edge research in artificial intelligence, focusing on areas such as machine learning, deep learning, NLP, and computer vision.
• Design, develop, and implement novel AI algorithms and models.
• Conduct rigorous experimentation and validation of research hypotheses.
• Publish research findings in leading academic conferences and journals.
• Collaborate with software engineers to deploy AI models into production systems.
• Mentor and guide junior research scientists and engineers.
• Stay abreast of the latest advancements in AI and emerging technologies.
• Identify new research opportunities and contribute to the strategic direction of AI development.
• Contribute to the development of intellectual property and patents.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 10+ years of post-Ph.D. research experience in AI/ML.
• Demonstrated track record of significant contributions to the field of AI, evidenced by publications, patents, and open-source contributions.
• Expertise in one or more core AI areas (e.g., deep learning, reinforcement learning, NLP, computer vision).
• Proficiency in programming languages such as Python and experience with ML frameworks (e.g., TensorFlow, PyTorch).
• Experience with large-scale data processing and distributed computing.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong leadership and communication abilities, with the capacity to explain complex concepts to diverse audiences.
• Proven ability to work independently and drive research projects to completion in a remote setting.

• Collect, clean, and process large sports-related datasets.
• Develop and apply statistical models to analyze player and team performance.
• Create predictive models for game outcomes, player development, and strategic planning.
• Visualize data and present findings through reports, dashboards, and presentations.
• Collaborate with coaches, athletes, and management to provide data-driven insights.
• Identify trends and patterns in sports data to inform decision-making.
• Stay updated on the latest advancements in sports analytics techniques and technologies.
• Ensure data integrity and accuracy throughout the analysis process.
• Contribute to the development of new analytical tools and methodologies.
• Communicate complex analytical concepts to diverse audiences.

• Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field. A Master's degree is preferred.
• Minimum of 3 years of experience in data analysis, statistical modeling, or a similar role, preferably within the sports industry.
• Proficiency in programming languages such as Python or R.
• Strong knowledge of SQL and database management.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Solid understanding of statistical concepts and machine learning techniques.
• Deep knowledge and passion for one or more sports.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation abilities.
• Ability to work independently and manage projects in a remote environment.

• Lead the development and implementation of advanced statistical models and analytical frameworks for sports performance.
• Analyze vast datasets related to player statistics, biomechanics, game events, and training data.
• Translate complex data findings into actionable insights for coaches, athletes, and management.
• Develop and maintain data visualization dashboards and reports to effectively communicate key metrics.
• Identify trends, patterns, and predictive indicators to optimize training regimens, injury prevention, and game strategies.
• Collaborate with coaching staff and sports scientists to understand their analytical needs and provide tailored support.
• Stay current with the latest advancements in sports science, data analytics, and relevant technologies.
• Manage data integrity and ensure the accuracy and reliability of analytical outputs.
• Mentor junior analysts and contribute to building a data-centric culture within the organization.
• Present findings and recommendations to stakeholders at various levels.

• Master's degree or Ph.D. in Sports Science, Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 6 years of experience in sports analytics or a closely related field, with a demonstrable track record of impacting performance.
• Proficiency in statistical programming languages such as R or Python, and experience with relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Expertise in data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong understanding of sports-specific data collection methods and performance metrics.
• Experience with database management and SQL.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to convey technical information to non-technical audiences.
• Ability to work independently, manage projects, and thrive in a remote team environment.
• Passion for sports and a deep understanding of athletic performance principles.