Applied Scientist, AWS Product Analytics

Key Skills

Java Programming, Python Programming, C++, SQL, AWS, Machine learning techniques, Deep Learning, Keras software library, PyTorch, TensorFlow, MxNet, Caffe, Lambda

Job Description

Job summary
AWS Product Analytics is looking for a world class applied scientist to join its Machine Learning team to build and expand a large-scale, established ML product directly impacting AWS product decisions and customer experiences. At AWS Product Analytics, you will invent, implement, and deploy infrastructure and systems for state-of-the-art machine learning algorithms. You will interact closely with our customers across Product and Engineering and surrounded by a team of exceptionally talented engineers, scientists, and academics with diverse backgrounds.

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.

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.

Key job responsibilities
As an applied scientist on product analytics team, you will play a key role in the AWS product decision making and long-term strategy. You will leverage your strong background in Computer Science and Machine Learning to help build our model development and assessment pipeline, harness and explain rich data at AWS scale, and provide automated insights to improve machine learned solution critical to AWS product decisions. You will be driving many scientific breakthroughs to ensure our ML models run smoothly, efficiently, and optimize for accuracy and speed. In partner with SDEs and Data Scientists on the team, you are responsible for innovation aimed at developing and step-changing our core ML product, operationalize the end to end solution with strong production mindset, and ensure the solution scales as we keep expanding our coverage across services and regions. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations.

The ideal candidate will be an independent thinker who can make convincing, information-based arguments. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. This person will have sound judgment and help recruit and groom high caliber science talent.

About the team
The AWS product analytics team is within a larger Data science, Business Intelligence & Data engineering team that focuses on broad data exploration, quantitative methodology, and statistical modeling to drive actionable data intelligence in AWS. Over last 5 years, the team has established strong data and analytics foundations supporting 125+ AWS products and services. We are recognized as the team with deepest data domain knowledge for AWS data and setting the high-bar for data engineering standard across AWS. The product analytics team started as a research project two years ago and has evolved into a team of Scientists and Engineers owning critical researches across core AWS services along with established ML products with both internal and external customers. We have laid out the foundation and ready to scale. This is the perfect time to join us and take AWS product analytics to the next level.

BASIC QUALIFICATIONS

• MS degree or equivalent in Computer Science (CS), Computer Engineering (CE), Machine Learning (ML), or related technical field;
• 3+ years of professional experiences in coding and problem-solving using at least one programming language such as Python, Java, C++, etc;
• 2+ years of professional experiences in the field of AI, Machine Learning, Deep Learning and related technologies;
• 3+ years of professional experiences using Python and Machine and Deep Learning toolkits such as Keras, Tensorflow, PyTorch, MXNet and, Caffe;

PREFERRED QUALIFICATIONS

• PhD Degree in Computer Science/Engineering, Math or related field;
• 4+ years of experiences developing AI models in real-world environments and integrating AI/ML and other AWS services into large-scale production applications;
• Prior work experience as an applied scientist or a data scientist;
• Experience with AWS services related to AI/ML highly desirable, particularly Amazon EMR, AWS Lambda; SageMaker, Amazon S3, Amazon EC2 Container Service and etc;
• Experience with Semi Supervised learning technique;
• Sound theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning;
• Ability to acquire and process data efficiently using language such as SQL;
• Ability to convey mathematical results to non-science stakeholders;
• Strength in clarifying and formalizing complex problems;
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.