Amazon
Data Scientist II, AWS Managed Operations Data Science (MODS)
🌎Herndon, Virginia, USA
1d ago
Job Description
Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world!
Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.
The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions.
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.
Your product analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are and comfortable working with cross-functional teams and systems.
This position requires that the candidate selected be a US Citizen.
10012
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.
- Business Insights and Recommendations: Frame business problems into scalable solutions; translate complex data insights and model outputs into actionable recommendations that address the organization's strategic objectives.
- 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
- Prototype models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.
- Documentation & Continuous Improvement: Create, enhance, and maintain technical documentation
A day in the life
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Mentorship and Career Growth
We’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 Experiences
Amazon 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.
About the team
The MODS team is driven by a shared vision of achieving operational excellence through data analytics and machine learning. We provide actionable insights to allow our stakeholders to manage operational posture and operator experience and drive sustainable, safe, and efficient operations.
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.
We are a customer obsessed team driving lean operations in all of AWS through actionable insights and data strategies that drive process improvement. - 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- 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
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you.
The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions.
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.
Your product analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are and comfortable working with cross-functional teams and systems.
This position requires that the candidate selected be a US Citizen.
10012
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.
- Business Insights and Recommendations: Frame business problems into scalable solutions; translate complex data insights and model outputs into actionable recommendations that address the organization's strategic objectives.
- 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
- Prototype models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.
- Documentation & Continuous Improvement: Create, enhance, and maintain technical documentation
A day in the life
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Mentorship and Career Growth
We’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 Experiences
Amazon 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.
About the team
The MODS team is driven by a shared vision of achieving operational excellence through data analytics and machine learning. We provide actionable insights to allow our stakeholders to manage operational posture and operator experience and drive sustainable, safe, and efficient operations.
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.
We are a customer obsessed team driving lean operations in all of AWS through actionable insights and data strategies that drive process improvement. - 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- 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
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
