Head of Informatics

JOB PURPOSE

The Head of Informatics is a senior role accountable for providing leadership and setting strategy across technical domains that include our research computing infrastructure, partnership with IT, our company-wide initiatives on data management and governance, and automation scaleup including communication of strategy to senior executives. This role will lead the design, implementation, and operations of our research & process development data architecture, AWS strategy for informatics infrastructure and research data management, and automation. This role will guide our software engineering efforts, emphasizing best practices in testing and deployment; our data capture and processing projects, emphasizing data provenance and lineages from Research through Process Development; and our evolving data science efforts, managing interdependencies between various groups. This role will be responsible for leading company-wide initiatives on data management and governance, ensuring consistency across the organization and enabling efficient research and accurate regulatory filings. The ability to influence within and across functions and work in a highly collaborative, fast-paced environment will be critical for Sana to successfully leverage data for gene and cell therapies today and in the future.

DUTIES AND RESPONSIBILITIES

• Serve as chair of Sana's data governance committee for the management, governance, and quality of data across the company
• Continue to evolve our research computing, data management and architecture roadmap as the business scales including gap assessment, risk mitigation, and prioritization of projects and investments
• Educate the company in data literacy and encourage efforts to collect, manage, and use internal and external data to drive operational efficiency and better decision-making
• Lead the Informatics Infrastructure, Computational Engineering, and Automation teams to define requirements for off-the-shelf systems or development of internal customized systems and deploy high quality solutions that ensure stakeholder groups have access to data and analytics they need to achieve scientific and clinical outcomes
• Define clear responsibilities and lines of communication between Informatics Infrastructure, Computational Engineering, and Automation teams
• Guide research computing, including:
  • designing, deploying and maintaining cloud infrastructure
  • specifying, selecting, and implementing LIMS in the support of research
• Partner with the corporate IT team, ensuring smooth connections with corporate infrastructure, consistent policies and good security practices
• Own the connectivity of research and process development data to GXP systems to ensure consistent definition and capture of data into the data lake and advanced analytics platforms
• Support an engineering culture that balances best practices for developing, testing and deploying systems with the timely delivery of results in support of company objectives
• Steer the development of automated lab systems, enabling scalable generation and capture of data and its interdependencies.
• Ensure the development of a robust and reliable infrastructure for computational biology and data science; including standardizing foundational data, providing an efficient computing platform, and enabling reproducible results

QUALIFICATIONS

Basic Qualifications

• PhD in a scientific or technical discipline with 12+ yrs experience in industry. BA/BS or MS with 15+ yrs experience in industry; expert knowledge of technical principles and concepts with a focus on data strategy
• 5+ years of successfully building and managing larger teams (> 10 FTEs including Directors & above) in research computing, engineering and/or automation in a biotech setting
• Strong familiarity with laboratory automation, integration, and scaleup
• Strong understanding of software development practices and comfort acting as a product owner
• Demonstrated experience partnering with Research functions, running steering team meetings, developing training plans, and driving user adoption
• Experience in business analysis, processing mapping, strategic road mapping, and digital transformation
• Experience owning the development and ongoing operations of infrastructure that supports multiple research and development streams
• Experience managing the development and maintenance of a cloud-based computing infrastructure that supports the collection of research data, bespoke and standardized analyses of that data, and systems that allow researchers to visualize the results
• Exceptional verbal and written communication skills with past experience presenting strategic roadmaps to senior executive leadership, and negotiation skills
• Ability to work, influence, and gain consensus across multiple functions (R&D, PD, Manufacturing, Regulatory, Quality, and Clinical)
• Must be highly organized and have the ability to manage multiple initiatives with many stakeholders
• Proven track-record to collaborate effectively in a cross-functional matrix environment and lead through influence across functional and organizational lines

• Strong analytical, problem solving, critical thinking and decision-making skills
• Proven track-record adapting to increasing scope and complexity of work brought on by growth/change and managing through change and ambiguity
• Ability to engage in crucial conversations - providing and receiving feedback

Preferred Qualifications

• Experience with designing, deploying, and maintaining data management systems and automated end-to-end workflows from research through IND filings preferably in the gene or cell therapy space
• Owning (i.e. accountable) and leading infrastructure strategy for data management/storage/capture for a mid-size company
• Direct experience with evolving and deploying research data infrastructure to support growth of a smaller startup to a mid-size company with > 400 users
• Prior experience in successfully implementing, utilizing and leveraging outsourcing external consultant management strategies
• Demonstrated understanding of the software development lifecycle
• Strong understanding of research processes (e.g. molecular biology, cell engineering, in vitro/in vivo studies, pathology, AAV/lentiviral generation, sample management)