Data Management Quality Lead

Data Management Quality Lead Waltham, MA $81 - $88.7 Hour On-site Contract Job Title: Data Management Quality Lead Location: Waltham, MA (Hybrid) Duration: 12 Months Interview Process: 1 interview Teams/In Person- Teams Interview Length- 45 mins Purpose of the Role: We are seeking an experienced Computational Biology Data Infrastructure Contractor to design, build, and deploy scalable data sharing and visualization solutions for multimodal biological datasets. This role will bridge the gap between complex computational biology data and research scientists with limited computational backgrounds, enabling democratized access to cutting-edge genomic, proteomic, and imaging data through intuitive, AI-powered platforms. The successful candidate will establish infrastructure and processes that accelerate scientific discovery across client s research organization. Key Accountabilities: Data Management & Infrastructure Development: Design and implement robust data management systems utilizing SQL-type and relational databases, integrate with API and other bioinformatics platforms, and establish scalable data pipelines for multimodal biological datasets including scRNA-seq, bulk RNA-seq, WES, proteomics, spatial transcriptomics, and imaging data. Interactive Visualization Solutions: Develop and deploy interactive data visualization frameworks that enable intuitive exploration of complex, multidimensional biological datasets by users with varying levels of computational expertise, ensuring accessibility and user-friendly interfaces that support scientific decision-making. AI Agent Development & Deployment: Build, configure, and deploy AI agents specifically designed to address data sharing, exploration, and visualization needs across the organization, creating intelligent systems that can respond to user queries and facilitate data-driven insights without requiring extensive computational knowledge. AI Infrastructure & Logistics: Establish and maintain AI hosting infrastructures, including deployment pipelines, version control, monitoring systems, and governance frameworks that ensure reliability, security, and scalability of AI-powered solutions across the research organization. Process Optimization & User Enablement: Create comprehensive processes, documentation, and training materials that enable researchers with limited computational backgrounds to independently access, explore, and visualize multimodal biological data, fostering a culture of data democratization and self-service analytics. Essential Requirements: Bachelors Degree 3-5 years of previous experience Technical Expertise: Hands-on experience with data management systems, including SQL-type and relational databases, with demonstrated proficiency in database design, optimization, and maintenance Practical experience with API or similar bioinformatics data platforms Strong working knowledge of interactive data visualization frameworks (e.g., Plotly, Dash, Shiny, Streamlit, or similar technologies) Proven experience in analyzing and integrating multidimensional biological datasets including scRNA-seq, bulk RNA-seq, whole exome sequencing (WES), proteomics, spatial transcriptomics, and imaging data AI & Infrastructure Skills: Hands-on experience developing, deploying, and managing AI agents for data sharing and visualization applications Demonstrated expertise with AI hosting infrastructures, including cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and MLOps practices Experience building operational logistics around AI systems including monitoring, maintenance, and governance Communication & Collaboration: Proven ability to translate complex technical concepts into accessible solutions for non-computational audiences Strong documentation skills and experience creating user-friendly guides and training materials Excellent stakeholder management and ability to gather requirements from diverse scientific teams Desirable Requirements: Experience working in pharmaceutical, biotechnology, or academic research environments Familiarity with bioinformatics workflows and computational biology best practices Knowledge of data governance, security, and compliance requirements in regulated industries Experience with version control systems (Git) and collaborative development practices Background in biological sciences or bioinformatics Experience with modern web development frameworks and API design Familiarity with data catalog and metadata management systems Key Deliverables: The primary outcome of this role will be the establishment of a comprehensive data sharing infrastructure and multimodal data exploration platform that enables researchers across the organization to independently access, visualize, and derive insights from complex biological datasets without requiring advanced computational skills. This includes deployed AI agents, interactive visualization tools, documented processes, and training resources that democratize data access and accelerate scientific discovery.