Remote or onsite in San Francisco and Austin. H1B visa transfer available.
HireStarter's client is a mission driven start-up looking to stop the spread of infectious disease. This is an opportunity to become a foundational member of the data science team and build the epidemiological models based on coupled rate equations, Monte Carlo simulations, LSTM neural networks and other machine learning techniques to forecast the spread of infectious disease. You will also help improve the existing illness signal, derive new signals based on proprietary symptoms and fever data, as well as external data. The ideas, research, and tools you develop will contribute directly to the realization of the company's mission. This role offers a flexible work environment.
The ideal candidate is skilled in a range of general data science, machine learning and other statistical approaches; has the engineering experience to build prototypes around these tools, and has extensive experience with modeling and forecasting, ideally in epidemiological context. You’ll be comfortable working cross-functionally with internal and external stakeholders. You understand how to work in a scrappy startup environment, and know how to balance speed vs. accuracy.
Advanced quantitative degree -- e.g. Statistics / Biostatistics, Physics, Computer Science -- MS/PhD preferred
5+ years industry experience in a relevant quantitative field, ideally at a high growth / early stage company
A proven track record of building forecasting models
A proven track record of working with large structured & unstructured data sets to extract timely, meaningful and impactful insights
Strong programming skills in SQL and Python (pandas, sci-kit learn, keras, tensorflow, etc.)
Experience with machine learning techniques
Business acumen & product intuition -- you must be able to think creatively and independently
Persuasive oral and written communication skills