Data Science Manager
On the Data Team at Ginkgo Bioworks, our focus is the strategic application of data science and engineering across the business. We tackle diverse problems that span molecular biology, robotic automation, finance & business strategy, and operations, all in service of supporting data-driven decision-making. We do that through a combination of durable software tools, closely embedded analysts, and side-by-side collaboration with data engineering.
As a Data Science Manager, you’ll join a distributed, highly collaborative team composed of data engineers, analysts, and data scientists with a wide range of backgrounds and experiences (the majority of the team is currently located in Boston and Seattle). You'll partner closely with scientific collaborators from across Ginkgo to develop analysis plans, deliver durable reports, on-board and train partners, and work with data scientists and engineers to design data-driven software tools. Ideal candidates are self-starters with a strong technical background who can identify opportunities to solve problems with data. Candidates should be curious and eager to learn about both the science and the business, possess analytical skills and reasoning, be a strong leader who can mentor and grow the team, and excel at communicating the team's work to broad audiences.
Every day we face new technical and scientific challenges that require deep cross-functional collaboration and novel solutions. Success in this evolving field is only possible with teams that represent diverse people, ideas, backgrounds, experiences, and ways of working. Active inclusion is core to how Ginkgo wins. We encourage individuals from underrepresented backgrounds to apply.
*Leading high-output technical team; building and nurturing team culture, coaching, and creating personalized development plans for all team members from entry-level to principal
*Delivering end-to-end data products, i.e. ability to work across the product lifecycle from exploration and discovery, to operationalization and production
*Project management including managing complexity and making informed trade-offs to quickly escape rabbit holes and make on-time deliveries
*Breaking down complex technical and quantitative topics for audiences with mixed levels of technical expertise; in particular, translating technical and scientific concepts into business outcomes and recommendations is essential for success in this role
*Comfort and aptitude for presenting progress, insights, and recommendations to stakeholders and senior leadership
*Storytelling with data, specifically supporting data-driven decisions with compelling visualizations
*Building strong partnerships with collaborators and stakeholders, influencing and collaborating at all organizational levels
*Willingness to work on a distributed team and adhere to common working hours across time zones
*Minimum requirement of quarterly travel to headquarters in Boston, MA
*Must be able to start the day at 10am EST and have familiarity with communication strategies and tactics for managing a distributed team
*Strong working knowledge of SQL and the ability to self-serve with basic data exploration tools like Tableau
*Software development best practices including story estimation, test-driven development, code review, and version control with git
*Excellent written and verbal communication skills
*Strong technical writer and documenter
*Fluency and practical experience with statistical methods like exploratory data analysis, hypothesis testing, power analysis, regression, and generalized linear models, as well as familiarity with advanced methods like time-series and survival analysis
*Fluency and practical experience with machine learning concepts and algorithms in supervised and unsupervised learning settings; examples include general machine learning workflow, linear/logistic regression, decision trees, neural networks, clustering, etc.
*Fluency and practical experience with data visualization techniques and best practices
Preferred Capabilities and Experience
*Experience with Agile workflow practices and familiarity with Atlassian tools including Jira, and Confluence
*Experience with the Amazon Web Services ecosystem
*Familiarity with biological data, specifically in the context of high-throughput screening
We also feel that it’s important to point out the obvious here – there’s a serious lack of diversity in our industry, and that needs to change. Our goal is to help drive that change. Ginkgo is deeply committed to diversity, equity, and inclusion in all of its practices, especially when it comes to growing our team. Our culture promotes inclusion and embraces how rewarding it is to work with people from all walks of life.
We’re developing a powerful biological engineering platform, so we must remain mindful of the many ways our technology can – and will – impact people around the world. We care about how our platform is used, and having a diverse team to build it gives us the best chance that it’s something we’ll be proud of as it continues to grow. Therefore, it’s critical that we incorporate the diverse voices and visions of all those who play a role in the future of biology.
It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees and employment applicants.