Amazon QuickSight Q is looking for a curious and customer obsessed Data Scientist with superior analytical skills. In this role, you will be focused on analytical efforts to help the team deeply understand our customers and data to drive decisions at all levels of the organization.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Key job responsibilities
• Design and implement measurement for the relevance of our training and benchmark data to customer production use cases.
• Engage in experimentation, proof of concept, and exploratory efforts to find opportunities to delight our customers with opportunities to discover novel insights about their data.
• Use your deep expertise in statistics (regressions, multilevel models, structural equation models, etc.), and data collection in a variety of settings (e.g., field studies, surveys, existing large data sets) to define and answer nebulous problems.
• Leverage your quantitative background to develop and test theoretical frameworks and design experiments.
• Work with colleagues across Science, Data Collection, and Engineering Teams to build scalable programmatic data analysis aimed at measuring the quality, complexity, robustness, and composition of customer, benchmark, and training data.
If you are passionate about data driven innovation, obsess over customers, and love solving complex problems in novel ways, please apply!
About the team
Q is a machine learning-powered natural language capability that empowers business users to ask questions about all of their data using everyday business language and get answers in seconds. For example, users simply type “what is our year-over-year growth rate” and get an instant answer in QuickSight as a visualization.
• 2+ years in a research science, ML, or data scientist role and a track record of strong statistical analysis and building machine or deep learning models.
• Experience in NLP data processing, applying algorithms to identify and extract natural language rules
• A Bachelor or Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.).
• Experienced in using multiple statistical/data science methodologies to solve complex business problems.
• Strong background and experience using Python with handling large data sets using SQL in a business environment.
• Excellent verbal and written communication. Strong ability to interact, communicate, present, and influence within multiple levels of the organization
• Master's or PhD in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least three years of working experience as a Data or Research Scientist.
• Experience presenting both the methodologies used and results for data science projects.
• Demonstrable track record of dealing well with ambiguity, ability to self-motivate, prioritizing needs, and delivering results in a dynamic environment.
• Combination of deep technical skills and business savvy to interface with all levels and disciplines within our and our organization
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.