Head of Engineering and Data
Biobot Analytics · Boston, MA/New York, NY
Health & Well-BeingPosted 1 month ago
In this role you will be responsible for leading the team delivering Engineering and Data solutions for Biobot’s “Data as a service” customers. You will work with key stakeholders across the company from Labs, Science, Business and Product to harvest our growing dataset, lead the construction of the appropriate technology and data components to deliver our digital product offerings that elevate and deliver valued and thoughtful insights to Biobot customers.
What will you do
- Lead Biobot’s engineering and data teams.
- Establish the formal structure and operation of the team(s), define processes and foster a data-driven, delivery oriented culture within the organization in order to help propel Biobot as a leader in data science, public health, and data for social impact.
- Establish best practices for data science at Biobot, including tracking and sharing exploratory data analyses, versioning data, sharing insights across the organization, and communicating our work publicly to relevant communities.
- Develop the technology platform architecture for Biobot’s data products, including technology choices and talent needed to deliver on core strategy anchors - visualization / dashboard technology (at scale), databases, APIs and the accompanying technology anchors required for compliance, security and governance.
- Provide technical vision and individual contribution where needed as we build our engineering platform to support evolving business needs
- Supervise and manage the team of data engineers developing robust data pipelines which process our data into community health insights presented to our customers. Establish best practices in data collection, curation, and management across the organization. Incorporate best practices around data equity and representation into decision-making processes at all levels of the organization.
- Participate heavily with the Biobot executive team and peers, help set business and technology strategy, represent product data science, initiate and debate key strategic topics and opportunities from your team’s work, and drive bold high-impact decisions.
- Bachelor’s or Master's degree with 8+ years of relevant experience in Cloud hosted platform development (SAAS or PAAS), with demonstrated experience delivering production grade products at scale. Exceptional candidates without an advanced degree but with a demonstrated history of equivalent relevant experience are encouraged to apply.
- 5+ years of experience in managing and mentoring data science and engineering teams in a high scale technology company.
- Exceptional track record as a strong and inclusive coach, providing feedback and mentoring to fellow team members.
- Hands-on experience with hosted cloud environments such as AWS, Google Cloud and/or Azure is required; prior experience with deploying web applications developed using React / Node.JS and powered through APIs is highly desirable.
- Demonstrated ability to communicate technology concepts across a broad range of audiences, including the company executives, in-house technical experts and when needed, customers.
- Knowledge of best practices and high-quality data sources, especially as it relates to public health and population data. Be able to assist the team to rationalize governance objectives pertaining to clinical and epidemiological data systems, including requirements for data privacy, accuracy, and security (HIPAA, etc.).
- Define and drive execution against core KPIs that govern the team’s progress, measurement of impact and effectiveness against company and team goals.
- Ability to lead organizational change by influencing others across various functions and navigating the team through new processes and/or technical advances.
- Being able to facilitate trade offs, rationalize timelines based on available staffing and time relative to company roadmap is critical.
- Commitment to building and supporting diverse and inclusive technical teams. Experience with building and managing productive and engaged product development teams
- Exposure and experience with data science, applied statistics, epidemiology, geospatial analysis, computational biology, or related fields is immensely beneficial.
- Familiarity with modern software engineering best practices, including iterative/agile development, scientific software development lifecycles, version control, troubleshooting and testing, as is the ability to make project decisions independently.
At Biobot, we believe that the best technologists can improve society and we strive to build a workplace in which everyone can thrive. Our goal is to be a diverse team that is representative, at all job levels, of the society we live in. We encourage applications from women; non-binary, trans, and gender-non conforming individuals; Black and indigenous individuals, and people from other minority racial and ethnic groups; and other groups traditionally underrepresented in technology startups.