Key Responsibilities
● Drive Data Equivalency: Design and execution of study migration checks to formally assess and ensure data and output equivalency between legacy platforms (HPC and MS Azure) and the novel data analysis environment (AWS based).
● Validation & Quality Assurance: Meticulously check data for completeness and correctness post-migration, troubleshooting and resolving any discrepancies to maintain the highest standards of data quality.
● Script Migration & Adaptation: Assist study team’s adaptation of existing Python scripts from legacy systems to the new AWS workspace, ensuring they are optimized for performance and reliability.
● User Onboarding & Support: Develop and deliver comprehensive onboarding materials, documentation, and training sessions to empower the team. Provide ongoing expert support to facilitate a smooth adoption of the new platform.
● Cloud Environment Management: Assist in the creation and configuration of cloud workspaces and analytical environments tailored to the needs of specific studies and analysis tasks.
● Independent Problem Solving: Proactively identify potential issues, bottlenecks, or risks in the migration process and independently develop and implement effective solutions.
● Stakeholder Collaboration: Collaborate closely with study stakeholders to align on migration priorities, provide progress updates, and ensure the new platform capabilities meet their research needs.
Who You Are
You are a detail-oriented and self-reliant individual with a strong sense of ownership. You thrive in a collaborative environment where your technical expertise can directly empower your peers and advance scientific goals. You are adept at working effectively in a hybrid and multi-cultural team environment.
Required Qualifications & Experience:
● University degree in Data Science, Computer Science, Bioinformatics, or a related quantitative field.
● 3+ years of professional experience in a data analysis role, with a proven track record of working with sensor data.
● Demonstrated, hands-on experience in performing data equivalency analysis and system-to-system data migration projects.
● Strong proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, SciPy).
● Solid understanding of and practical experience with cloud computing environments, preferably AWS.
● Excellent problem-solving skills and the ability to work independently to troubleshoot complex technical and data-related issues.
● Strong communication and interpersonal skills, with an ability to explain complex concepts to a diverse audience.
Desired Qualifications:
● Experience with the R programming language.
● Familiarity with working in a regulated (e.g., GxP) environment and handling clinical study data.
● Experience in creating technical documentation, training materials, or user guides.
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