Are you passionate about big data and machine learning? Do you enjoy solving complex analytical problems, build predictive analytics models and develop insights and recommendations at web scale? Do you want to make an impact in Amazon’s multi-billion-dollar Messaging business? Amazon’s Outbound Communication Services, OCS, owns foundational systems that power all of Amazon's customer-facing communication on Email, SMS, Push channels, and other emerging messaging applications. In 2019, we sent over 135 billion messages to our global customers on these channels! OCS builds self-governing and message-optimizing engines that leverage integrated Machine Learning, massive data processing and adaptive algorithms to deliver the best messages to Amazon’s customers, over the best channel, and at the right time. Our systems ensure best-in-class engagement experience, which spans transactional and marketing communications. We're building a top-notch team of engineers, applied scientists, data engineers, and engineering leaders. The problems we face are complex and interesting including information engineering, data mining of Big Data sets, and governing real-time messages at scale. We build large scale, distributed systems using multiple AWS services that we designed from the ground up.
We are looking for a strong Applied Scientist to work backwards from customers, create models and develop insights, deliver impact, and drive growth of the OCS worldwide. As a Senior Applied Scientist on our team, you will be working with business stakeholders, product/program managers, developers and executives to deeply understand customer problems and priorities. You will form hypotheses, analyze the corpus of Outbound and Amazon data using statistical methods, build predictive models, generate recommendations to address a range of problems to optimize the value of the messages we send to our customers. These span developing insights on customer engagement trends, building models to inform message rates, channel selection, and defining segmentation for marketing, etc. Your expertise will enable us to enable new customer experiences while maintaining best-in-class customer experience. You will be comfortable with big data systems, intimately familiar with advanced machine learning and statistical methods, and experienced in applying these to solve business problems. You will have a strong bias towards customer obsession and delivering results while dealing with ambiguity in fast-paced dynamic environments.
Roles and Responsibilities
· Work with business teams, product/program managers, engineers and leadership to identify and prioritize customer and business problems
· Translate these problems into specific analytical questions and form hypotheses that can be answered with available data using statistical methods or identify additional data needed in the master datasets to fill any gaps
· Perform hand-on data analyses and modeling with huge datasets to develop insights and recommendations to inform decisions across the program
· Design and run A/B experiments to validate the hypotheses and evaluate the impact of your optimizations and communicate your results to various stakeholders
· Collaborate with engineers and product managers to build scalable solutions and new capabilities
· Help on projects of high visibility across the organization and deliver business impact
· Masters in Computer Science, Engineering, Statistics or related field
· Experience working with business stakeholders, identifying and prioritizing requirements, building models, conducting analyses and developing insights to enable decisions
· Excellent analytical and problem-solving skills
· 3+ years of experience in statistical modeling tools (e.g., R), scripting languages (e.g., Python, Scala), relational data systems and data warehouses
· 2+ years of experience in big data systems and machine learning techniques
· Strong verbal and written communication and data presentation skills
· Familiarity with using data visualization tools
· Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
· Experience giving data presentations
· PhD in Computer Science, Engineering, Statistics or equivalent experience
· Ability to think innovatively and creatively about complex technical and business problems
· Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams
· Experience working with web-scale data sets and distributed computing tools (e.g., Map Reduce, Hive, Spark)
· Experience with AWS technologies like Redshift, S3, EC2, Data Pipeline, EMR, AML, etc.
· Knowledge of professional software engineering practices & best practices across the full software development life cycle
· Publications or presentations in recognized Machine Learning, Deep Learning or Data Mining journals/conferences
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