Senior Data Scientist - Human-in-loop ML/AI Services

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

Interested in Machine Learning (ML) and Artificial Intelligence (AI)? Our team's mission is to make machine learning easy, stronger, and universal across data driven products and businesses. Our vision is to bring the best of humans and ML/AI algorithms to improve the entire machine learning model development lifecycle (the loop). We specialize in developing managed Human-in-loop ML/AI services (HIL) such as SageMaker Ground Truth for model training, Amazon Augmented AI for model inference, and Mechanical Turk for crowd intelligence. Our strategy is to bring the best of ML based automation to tasks such as ground truth generation via active learning and online learning approaches. Similarly, we provide powerful (human+machine) solutions for improving the efficiency of human processes via Augmented Artificial Intelligence.

We are seeking an experienced Senior Data Scientist for the Human-in-loop ML/AI Services team. This is a role that combines data science leadership, organizational ability, technical strength, product focus and business understanding. It will be your job to help develop data science solutions for human-in-loop problems. You will work closely with the product and engineering teams to ship them to our customers. You are also expected to advise the HIL leadership team, mentor junior engineers and scientists and be a role model for Amazon Leadership Principles.

Strong technical skill and experience doing doing data science are required. Our customers are strongly technical and the solutions we build for them are strongly coupled to technical feasibility.

If you are ready for the challenge, come and help us design the future.

About Us

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. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

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.

BASIC QUALIFICATIONS

• Graduate degree (M.S or Ph.D) in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
• Experience building and applying Machine Learning and analytic solutions to strategic business problems
• Demonstrated thought-leadership with a passion for translating data into action and business insights.
• Excellent written and verbal communication skills and good management and leadership experience in applying quantitative solutions. Must have demonstrated ability to explain analytical techniques and strategies to executives and non-scientist audiences·
• 5+ years of experience working in data science. Skilled with Python, Java, C++, or other programming language, as well as with R, SAS, MATLAB, or similar scripting language.

PREFERRED QUALIFICATIONS

• Advance degree (PhD) in Computer Science, Applied Math or a related field
• Advanced knowledge of big data analytics technologies and experience applying them to very large data sets, users, and customers
• Knowledge of cloud computing and AWS services
• Experience with data visualization software such as Tableau or Quicksight
• Meets/exceeds Amazon’s functional/technical depth and complexity for this role
• Meets/exceeds Amazon’s leadership principles requirements for this role