Who We Are
Stratus Data is a consultancy that enables industry leaders to solve their most pressing challenges using data science. We’ve collaborated with research teams at top institutions like Harvard and Stanford, as well as at companies like General Electric and 21st Century Fox. Our past projects include:
- Data Infrastructure
- Business Intelligence
- Machine Learning
- Medical Devices
We are remote-first, with a strong presence in the San Francisco Bay Area.
Who You Are
Stratus Data is looking for a Data Scientist with a Ph.D., or Masters with 3+ years of applied technical experience to join us in driving organizational impact. The candidate will be responsible for developing data pipelines, analyses, and reports; and communicating the results to both technical and executive business audiences. The ideal candidate possesses strong situational and interpersonal awareness, an understanding of the business context they operate in, a tireless pursuit to grow, and a curiosity for the “why” beyond the “what”. Integrity and fast thinking are a must. Most of all: empathy. Our job is to marry organizational challenges to data science solutions.
What You’ll Do
- Analysis and Reporting: interrogate data in order to generate actionable insights; develop presentations and interactive reports enabling leaders to grow and act.
- Data Modeling and Analytics Engineering: design scalable data models that transform raw data to consumption-ready data for analytical and business audiences. Develop efficient and robust data pipelines that support the data models you design.
- Communicating: synthesize technical developments and key findings into reports and presentations that will inform executive decision making at clients.
- Teaching and Learning: develop curricula and content that enable the Stratus team to grow through what you learn.
What You’ll Bring
- Ph.D. in Engineering, Applied Math, Science, or equivalent; OR Masters in Engineering, Applied Math, Science, or equivalent and 3+ years of work experience.
- Extreme thoroughness and attention to detail.
- Ability to communicate complex subjects to technical and non-technical audiences.
- Strong orientation towards collaboration and enabling peer growth.
- Experience with software engineering, applied machine learning, applied statistics, or optimization.