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Amazon Data Scientist II AWS Managed Operations Science MODS 
United States, Kansas 
723122988

Today
DESCRIPTION

The AWS Managed Operations Data Science (MODS) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration and feature engineering and ETL to model development. You will leverage a diverse set of tools and technologies, including SQL, Python, Spark, Hugging Face and various machine learning frameworks, to tackle complex business problems and uncover valuable insights.This position requires that the candidate selected be a U.S. citizen.Key job responsibilities
- Collaboration & Cross Functional Relationships: Interact with business and software teams to understand their business requirements and operational processes
- Data Exploration and Analysis: Conduct in-depth exploratory data analysis to understand the structure, quality, and patterns within complex datasets. Apply statistical and machine learning techniques to extract insights, identify trends, and uncover hidden relationships in the data.
- Data Pipeline and Infrastructure: Contribute to the design and implementation of data pipelines, data lakes, and other data infrastructure components to support the organization's data-driven initiatives.
- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics- Documentation & Continuous Improvement: Create, enhance, and maintain technical documentation
A day in the life
Why AWSUtility Computing (UC)Work/Life BalanceMentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Diverse ExperiencesAmazon 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.
We define, monitor, and predict metrics to provide recommendations on AWS operations that are diagnostic (why something happened), predictive (what will happen) and prescriptive (best course of action) in nature.This position requires that the candidate selected be a U.S. citizen.

BASIC QUALIFICATIONS

- 3+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
- Master's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 2+ years' experience in Data Science or related Science discipline, OR, Bachelor's Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with 5+ years' experience in Data Science or related Science discipline


PREFERRED QUALIFICATIONS

- 6+ years of data scientist experience
- 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience in a ML or data scientist role with a large technology company