Staff AI/ML Data Scientist
Menlo Park
Applications have closed
One Concern
Our mission is to make disasters less disastrous. We integrate hazard science with cutting edge AI/ML to help customers uncover their blindspots, and make better decisions. %One Concern is a Menlo Park-based benevolent artificial intelligence company with a mission to increase the global community's resilience to natural hazards. Founded at Stanford University, One Concern enables cities, corporations and citizens to embrace a disaster-free future, through AI-enabled technology, policy, and finance. By combining data science and natural phenomena science we are pursuing a vision for planetary-scale resilience, where everyone lives in a safe, equitable, and sustainable world.
One Concern is seeking a Staff Data Scientist, AI/ML to join our team at One Concern. This role will work on developing innovative machine learning models for a variety of applications in flood and resilience modeling. You should have experience with collecting and cleaning data, feature engineering, building scalable machine learning algorithms and constantly improving them over time. You should be a visionary, executor and an excellent communicator.We work in a highly collaborative, challenging and exciting environment. Our data science and engineering challenges are unique, so you should be comfortable stepping in uncharted territory and excited to create systems that can scale to all disasters and geographies. If you are a problem solver, think out-of-the-box, love challenging yourself, and want to work for a cause, we would love to have you at One Concern.
We are committed to a workplace that reflects the community we serve. We especially encourage women, people of color, and others who are underrepresented in the tech industry to apply.
Responsibilities
- Work closely with data science and engineering team to identify areas of improvement and propose creative solutions to product challenges
- Design and Develop custom machine learning models to drive innovative business solutions
- Work with domain experts in building and improving different products
- Assess the potential usefulness and validity of new approaches and data sources
- Formulate your own problems as the problem might not always be defined for you
- Work in an agile, collaborative environment, partnering with other domain scientists of all backgrounds and disciplines to bring analytical rigor and statistical/ML methods to solve challenges
Requirements
- Have a track record of coming up with new ideas or improving existing approaches in machine learning
- Possess the ability to own and pursue a research project, including impactful problems and individually carrying it out to completion
- Strong background of machine learning, deep learning, statistics and quantitative analytics
- At least 5 years of applying machine learning for solving real-world problems in industry
- Past delivery of large-scale ML solutions for complex business problems
- Advanced experience with Python (preferred)
- Proficiency in using one or more query languages such as SQL
- Advanced degree in Machine Learning or Artificial Intelligence, Computer Science, Statistics, Mathematics or related field
Nice to have
- Experience working on applying machine learning methods on geospatial data to solve real world problems is a big plus
- Experience with GCP and big data technologies such as hive, hadoop, spark etc.
- Domain knowledge in flooding, earthquake, damage prediction is a plus
Tags: Agile Big Data Computer Science Deep Learning Engineering Feature engineering Finance GCP Hadoop Machine Learning Mathematics ML models Python Research Spark SQL Statistics
Region:
North America
Country:
United States
Job stats:
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