Quantitative Researcher

About us: WeatherBill is a technology company based in San Francisco that helps people and businesses adapt to climate change. We are dedicated to making a difference in the lives of our customers around the globe by managing their weather risks. We protect the $3 trillion global agriculture industry from the financial impact of adverse weather - the cause of over 90% of crop loss - with automated insurance products that farmers can customize and purchase online. Our technology also powers Raincheck.com , an automated weather insurance program for travelers worldwide.

Job description WeatherBill is aggressively hiring exceptional quantitative researchers to join our math team. We leverage big data and cloud computing to tackle real-world problems in climatology, machine learning, and risk management. Our extraordinary mission is to build a detailed statistical model of all possible weather events everywhere on Earth, so that every weather risk can be comprehensively managed using WeatherBill insurance products.

We are looking for people who

• play well with others
• enjoy thinking outside of the bell curve
• are comfortable working with huge, messy data sets
• know what SVD and SVM are
• say names like Dirichlet, Poisson, Cholesky, Markov, Kolmogorov in everyday conversation
• have thought seriously about how to win the Netflix Prize
• write elegant, modular, concise, production-quality code
• want to build massively scalable algorithms for adaptive signal processing, dimensionality reduction, Monte Carlo simulation, and more

• Advanced degree from a reputable university; training in meteorology or climatology is not required
• Unstoppable drive to solve problems, meet deadlines, and learn whatever is necessary along the way
• Excellent communication and collaboration skills
• Software development experience in a Linux environment; fluency in Python, Java or Clojure is preferred
• Experience applying sophisticated algorithms to big data; experience with MapReduce is a plus
• Deep applied knowledge of machine learning, stochastic processes, and Bayesian inference

• A driven, motivated and talented team
• Energetic, idea-driven and transparent work environment
• Opportunity and resources to work on challenging research problems
• Award-winning offices in the South Park neighborhood of San Francisco
• Catered lunches, well-stocked selection of beverages, perks
• Competitive pay and incentive stock options

_Contact_:
Please send your cover letter and curriculum vitae to Gary Jong gary@weatherbill.com or visit our careers website at www.weatherbill.com/about/careers/.