Data Scientist
Remote
Ginkgo Bioworks
Technical Excellence
- Experience working with biological data, specifically in the context of high-throughput screening is a plus
- Track record of delivering end-to-end data science products, i.e. ability to work across the product lifecycle from exploration and discovery, to operationalization and production
- Experience analyzing complex data, drawing conclusions, and making actionable recommendations
- Strong project management skills including managing complexity and making informed trade-offs to quickly escape rabbit holes and make on-time deliveries
- Experience with Agile workflow practices and familiarity with Atlassian tools including Jira, and Confluence is a plus
- 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, and deep skill in at least one visualization tool
- Software development best practices including story estimation, test-driven development, code review, and version control with git
- Deep Python skills including familiarity with pandas, scikit-learn, and advanced visualization libraries such as Altair, seaborn and matplotlib is preferred
- Extensive experience with SQL required. Experience working with NoSQL data environments and tools such as Hadoop, Spark, DynamoDB is a plus
- Experience writing and maintaining ETL workflows with tools like Airflow or Luigi is preferred
- Experience with the Amazon Web Services ecosystem is a plus
Relationships and Communication
- Excellent written and verbal communication skills are required
- Aptitude for 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 work progress, insights, and recommendations to stakeholders and senior leadership
- Willingness to work on a distributed team and adhere to common working hours across time zones. Familiarity with communication strategies and tactics for distributed teams is a plus
- Strong technical writer and documenter
- Track record of storytelling with data, specifically supporting data-driven decisions with compelling visualizations using tools like Tableau, seaborn / Altair, and/or ggplot2 / shiny
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow Biology Data analysis Data visualization DynamoDB EDA Engineering ETL Excel Finance ggplot2 Git Hadoop Jira Machine Learning Matplotlib NoSQL Pandas Python Scikit-learn Seaborn Spark SQL Tableau TDD Testing
Perks/benefits: Career development Startup environment
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