Gene Security Network
Senior Statistician and Programmer



Full Job Title: Senior Statistician and Programmer 
Position Type: Senior Research and Development Statistician at NIH/Venture-Backed Startup 

Company: Gene Security Network 
Compensation: Starting salary $80k-$140k,depending on qualifications and equity package. 
Employee Type: Full-time 
Industry: Healthcare, Biotechnology Complex Genetic Diagnosis 
Required Experience: At least 5 years working in applied statistics, preferably designing and coding 
production systems. 

Educational Background: Degree in Statistics at least at Master’s level; PhD preferred. Excellent programming in MATLAB or R, and preferably C or JAVA. Knowledge of biological sciences preferred. 

Req’d Travel: No 

Location: Mountain View, San Francisco Bay Area, with second office in Manhattan 

Managing:Initially no, but given range of Others statistical challenges and rapid growth, this could quickly grow to management position. 

The Organization:
Gene Security Network has developed a disruptive and proprietary technology to screen embryos for multiple genetic disorders and disease susceptibilities in the context of in-vitro fertilization (IVF). This approach involves analyzing DNA with high throughput genetic screens and advanced statistical techniques to reliably determine key disease-related genetic markers and chromosome copy numbers from a single cell. The technology enables clinicians at IVF centers to select embryos with the highest probability of becoming healthy babies, and enables parents to have children that do not have susceptibility to genetic conditions that are of concern to the family. The team consists of 22 doctors, statisticians, geneticists, laboratory technicians and software engineers mostly from Stanford, MIT and UCSF. Our technology has been funded by three grants from the National Institute of Health, partner IVF centers, a senior person within Google, the healthcare-focused venture capital firm CCV and the renowned Sequoia Venture Capital. GSN will begin offering this service for the five leading IVF centers around the United States in 2008. We will then offer the service internationally. 

Description 

You will be responsible for developing, refining and implementing statistical algorithms that are central to our strategic goals. This will involve leveraging your experience of basic statistics as well as more specialized topics such as machine learning, meta-analysis and optimization. These topics will be applied to advanced algorithms for determining genetic information with high confidence from limited amounts of genetic data such as single cells, or genetic data that is contaminated by other signals, and associating that genetic data with particular phenotypes such as susceptibility to particular diseases. More detailed job functions may include: 

• Refining, testing and implementing new algorithms in Matlab used to clean high-throughput genetic data for pre-implantation diagnosis in the IVF context. 
• Implement interfaces to the application server code so that the statistical results can be seamlessly integrated into reports for treating physicians. 
• Help in the development of laboratory studies and clinical trials for developing new protocols and extending GSN’s algorithms for cleaning high-throughput genotype data to other applications such as non-invasive pre-natal diagnosis. 
• Implement machine-learning algorithms for the generation of enhanced reports to aid in treatment decisions by doctors. 
• Contribution to NIH grants and papers that are submitted to journals such as Bioinformatics and Nature Genetics. 

Working Conditions: 
The team is a highly motivated and highly skilled group of professionals based in the San Francisco Bay Area but with members located around the world, including New York and Boston. 
The entire team meets virtually (Instant Messenger and conferencing) regularly during the week and in person once a month in Mountain View, CA. 

Qualification :
Statistics training at least to the Master’s level including classical statistics, ANOVA and multivariate regression, Bayesian methods, machine learning techniques, linear algebra and convex optimization. At least five years of experience coding in Matlab and/or R. Experience with the biological sciences and genetic data is preferred. Experience with the software development process is key and coding experience in C or JAVA is preferred. Candidate must have the ability to work in a team, and also to operate independently in setting priorities and developing goals. 

Application Details: 
Please send cover letter and resume to: John Croswell: jcroswell@genesecurity.net 

Equal Opportunity: 
Gene Security Network affords equal employment opportunities to all qualified persons,regardless of race, color, religion, national origin, age, sex, disability, sexual orientation, gender expression, veteran or marital status.