Katalyst CRO
Job Description
As a Data Analyst with a focus on App Development, you will play a crucial role in building applications that streamline data visualizations and empower bioinformatics and non-bioinformatics stakeholders. You will work closely with researchers to understand their needs and transform requirements into efficient, user-friendly software solutions. Your work will enable scientists to leverage data effectively, driving innovative research and development initiatives.
Responsibilities
App Development: Design, develop and refactor applications that enhance the accessibility and usability of genomic data, integrating user feedback for continuous improvement. Understanding User Requirements: Engage with bioinformatics research scientists to gather and analyze requirements, translating them into technical specifications and application features. Enabling Team Success: Collaborate with cross-functional teams to ensure applications are aligned with common data model standards and facilitate effective data management and querying. Process Automation: Utilize scripting languages to automate and optimize data processing/ingestion workflows, maintaining high standards of data quality and integrity. ETL Process Management: Develop and execute ETL processes that align with organizational standards, ensuring seamless integration of high-value datasets. Documentation and Collaboration: Maintain comprehensive documentation of development processes and version control to support collaboration and reproducibility.
Requirements
Bachelor's degree in computer science, bioinformatics, or a related field, with 3+ years of relevant experience. Proven experience in app development and user interface design (preferred: Rshiny). Strong skills in requirements gathering and translating them into actionable software solutions. Proficiency in PostgreSQL or similar databases, with the ability to write complex queries. Expertise in Python and R for automation and data manipulation. Familiarity with bioinformatics data and bioinformatics data standards. Excellent communication skills and a collaborative mindset, essential for partnering with diverse research teams. Experience with AWS. Experience in API development.
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As a Data Analyst with a focus on App Development, you will play a crucial role in building applications that streamline data visualizations and empower bioinformatics and non-bioinformatics stakeholders. You will work closely with researchers to understand their needs and transform requirements into efficient, user-friendly software solutions. Your work will enable scientists to leverage data effectively, driving innovative research and development initiatives.
Responsibilities
App Development: Design, develop and refactor applications that enhance the accessibility and usability of genomic data, integrating user feedback for continuous improvement. Understanding User Requirements: Engage with bioinformatics research scientists to gather and analyze requirements, translating them into technical specifications and application features. Enabling Team Success: Collaborate with cross-functional teams to ensure applications are aligned with common data model standards and facilitate effective data management and querying. Process Automation: Utilize scripting languages to automate and optimize data processing/ingestion workflows, maintaining high standards of data quality and integrity. ETL Process Management: Develop and execute ETL processes that align with organizational standards, ensuring seamless integration of high-value datasets. Documentation and Collaboration: Maintain comprehensive documentation of development processes and version control to support collaboration and reproducibility.
Requirements
Bachelor's degree in computer science, bioinformatics, or a related field, with 3+ years of relevant experience. Proven experience in app development and user interface design (preferred: Rshiny). Strong skills in requirements gathering and translating them into actionable software solutions. Proficiency in PostgreSQL or similar databases, with the ability to write complex queries. Expertise in Python and R for automation and data manipulation. Familiarity with bioinformatics data and bioinformatics data standards. Excellent communication skills and a collaborative mindset, essential for partnering with diverse research teams. Experience with AWS. Experience in API development.
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