Lead Data Scientist

POSITION SUMMARY:

Natera is seeking a highly motivated Lead Data Scientist to join our rapidly growing company. As a member of the data group you will participate in the design and prototyping of cutting edge algorithms for analysis of genetic and clinical data. You will perform data analysis and algorithm design, contribute to our intellectual property portfolio, and interact closely with R&D and product teams to define the requirements and improve our products and processes.

PRIMARY RESPONSIBILITIES:

• Lead the  research efforts in building Machine Learning/Deep Learning models for next generation sequence platforms
• Leverage Machine Learning/Deep Learning to build the next round of algorithms and products
• Move products through the full development process, from research through commercial launch
• Contribute to our intellectual property portfolio
• Drive rigorous data analysis effort and support group efforts toward high quality documentation
• Mentor team members and provide thought leadership
• Make decisions regarding own work methods, sometimes in ambiguous situations, and requires minimal direction and receives guidance where needed
• Help develop and guide molecular biology experiments

REQUIRED QUALIFICATIONS:

• Masters or Ph.D. in quantitative field (Computer Science, Applied Mathematics, Statistics, Bioinformatics, Engineering, or similar)
• At least five years of experience in data analysis using scripting languages such as Python
• Extensive knowledge and practical experience in machine learning, statistics, deep learning, and bioinformatics
• Experience leading the development and implementation of advanced analytical models and pipelines for processing and interpreting RNA and miRNA data
• Advanced experience in use of open source machine learning libraries (Python or R) in a cloud based environment
• Experience in large scale data processing
• Experience with a database query language such as SQL
• Experience with scalable data processing tools (Spark, Dataflow or similar)
• Proven ability to apply mathematical principles to solve real estimation problems and implement practical solutions
• Familiarity with assay development and analysis pipelines for molecular and clinical biomarkers
• Proven experience working with teams of diverse individuals to deliver complex projects
• Extensive experience in using Python, R, and Spark and leveraging numerical and machine learning libraries (NumPy, Pandas, scikit-learn, Tensorflow, etc.)
• Expert knowledge in Machine Learning, deep learning, statistical modeling, and bioinformatic pipelines
• Knowledge of human genetics and sequencing technologies

DESIRED QUALIFICATIONS:

• Previous experience in diagnostic testing
• Excellent communication skills and the desire to work in a dynamic and collaborative environment