2,999 Lead Pharmaceutical Research Scientist Remote Drug Discovery jobs in Kenya

• Lead and mentor a team of research scientists in the discovery and optimization of novel therapeutic agents.
• Design and implement innovative research strategies to identify and validate new drug targets.
• Oversee the execution of in vitro and in vivo studies to assess the efficacy, safety, and pharmacokinetic properties of drug candidates.
• Analyze and interpret complex biological and chemical data, drawing meaningful conclusions and making data-driven decisions.
• Develop and optimize assays for high-throughput screening and compound evaluation.
• Collaborate with computational chemists, biologists, and toxicologists to advance drug discovery programs.
• Prepare comprehensive research reports, manuscripts for publication, and patent applications.
• Present research findings at scientific conferences and internal meetings.
• Manage research budgets and ensure efficient resource allocation.
• Stay abreast of the latest scientific literature, emerging technologies, and industry trends in pharmaceutical research.
• Contribute to the strategic direction of the company's drug discovery portfolio.
• Ensure all research activities comply with ethical guidelines and regulatory requirements.

• Ph.D. in Pharmacology, Medicinal Chemistry, Biochemistry, Molecular Biology, or a related field.
• Minimum of 7-10 years of post-doctoral research experience in the pharmaceutical or biotechnology industry, with a focus on drug discovery.
• Proven track record of successfully leading research projects and contributing to the advancement of drug candidates.
• Extensive experience in designing and conducting biological assays, in vitro studies, and/or in vivo models.
• Strong knowledge of drug discovery principles, including target identification, lead optimization, and preclinical development.
• Proficiency in data analysis software and bioinformatics tools.
• Excellent leadership, team management, and communication skills.
• Ability to work independently and manage multiple research projects in a remote setting.
• Strong scientific writing and presentation skills.
• Experience with project management is a plus.

• Lead the design and execution of complex genomic data analysis pipelines, including next-generation sequencing (NGS) data.
• Develop and implement advanced statistical models and machine learning algorithms to interpret biological data and identify significant patterns.
• Collaborate closely with research scientists, bioinformaticians, and other data analysts to define research questions and analytical strategies.
• Manage and curate large-scale genomic datasets, ensuring data integrity, accuracy, and accessibility.
• Visualize complex data in a clear and comprehensible manner for scientific publications, presentations, and internal reports.
• Stay current with the latest advancements in bioinformatics tools, algorithms, and statistical methodologies.
• Mentor and guide junior data analysts and researchers in data analysis techniques.
• Contribute to the development of new research methodologies and data analysis platforms.
• Ensure reproducibility of analysis by maintaining well-documented code and workflows.
• Present findings to internal teams and external collaborators at scientific conferences.

• 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.

• 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.