Senior Data Scientist, Sales Insights, Analytics, Data Engineering & Science (SI

DescriptionAWS is seeking an experienced, self-directed Data Scientist to support Sales, Strategy, and Operations. They will be responsible for finding new ways of leveraging our large, complex data streams to help us serve our customers in their journey to the cloud.A successful candidate will collaborate closely with business stakeholders, product managers, and data engineers on high visibility and high impact initiatives. They will invent, implement, and deploy state of the art machine learning/AI algorithms and systems to understand our data using tools and techniques such as causal inference models. They will build prototypes and explore conceptually large-scale ML solutions. Beyond mathematical understanding, they have a deep intuition for machine learning that allows them to discover new insights and optimize our sales intelligence offerings. They are able to pick up and grasp new research and identify applications or extensions within the team. They are a superb written and verbal communicator.Key job responsibilitiesWork with business stakeholders, product managers, data scientists, and engineers to translate business problems into the right machine learning, data science, and/or statistical solutions.Execute every stage of the machine learning development life cycle; researching, developing, deploying, scheduling in production, measuring adoption, improving, and maintaining.Build state of the art causal inference models to help the business understand its key drivers.Work with large volumes of structured and unstructured data spread across multiple databases. Design and implement data pipelines to clean and merge these data for research and modeling.Use AWS services (AWS Redshift, S3, EC2, Glue, etc) to deploy scalable ML models in the cloud.Communicate insights to business owners in concise, non-technical language.Examples of projects include: propensity-to-buy prediction and explanation, product recommendation, forecasting, anomaly detection, text classification, generative AI content generation.About The TeamAWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Basic QualificationsBachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.4+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience.Experience with statistical models e.g. multinomial logistic regression.Experience managing data pipelines.Preferred QualificationsMaster's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive).Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue).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.

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