Data Scientist II, Amazon Special Projects

We are a team of doers working passionately to apply cutting-edge advances in technology to solve real-world problems. As a Data Scientist at the intersection of machine learning and the life sciences, you will participate in developing exciting products for customers.

Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment.

At the cutting edge of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams.

Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally.

We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.

We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

Key job responsibilities

• Deliver data analyses that optimize overall team process and guide decision-making
• Identify key metrics that are drivers to achieve team goals; work with senior stakeholders to refine your results
• Use modern statistical methods to highlight insights for predictive & generative ML models and assay process
• Perform correlation analysis, significance testing, and simulation on high- and low-fidelity datasets for various types of readouts
• Generate reports with tables and visualization that support operational cycle analysis and one-off POC experiments
• Deep dive to understand source of anomalies across a variety of datasets including low-level sequencing read data
• Collaborate with multi-disciplinary domain experts to support your findings and their experiments
• Write well-tested scripts that can be promoted by our software teams to production pipelines
• Learn about new statistical methods for our domain and adopt them in your work
• Work fluently in SQL and Python. Be skilled in generating compelling visualizations

A day in the life

New data has just landed and promoted to our datalake. You load the data and verify it's overall integrity by visualizing variation across target subsets.

You realize we may have made progress toward our goals and begin to test the validity of your nominal results. At midday you grab lunch with new coworkers and learn about their fields or weird interests (there are many).

You generate visualizations for the entire dataset and perform significance tests that reinforce specific findings. You meet with peers in the afternoon to discuss your findings and breakdown the remaining tasks to finalize your group report!

About the team

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme.

We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds.

If you’re interested in innovating at scale to address big challenges in the world, this is the team for you.

BASIC QUALIFICATIONS

• 2+ years of data scientist experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical / mathematical software (e.

g. R, SAS, Matlab, etc.) experience

• 3+ years of machine learning / statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience applying theoretical models in an applied environment

PREFERRED QUALIFICATIONS

• Experience in Python, Perl, or another scripting language
• Experience in a ML or data scientist role with a large technology company
30+ days ago