Sr. Data Scientist - Security, Global Services Security
The Global Services Security (GSS) team at AWS is seeking a talented data scientist to help lead adoption of AI/ML in our products and services.
The candidate will envision, experiment, prototype, and implement AI/ML solutions in our products to meet the needs of our customers.
This is a hands-on role where success is measured by the impact of the AI/ML solutions that meet our customer needs.
The GSS team leverages the expertise and ingenuity of our builders to establish scalable security solutions for both internal and external customers that drive business outcomes.
Our goal of securing the world's workloads and building a brighter future for humanity requires us to focus on reliable delivery of bar raising security outcomes and investment in security mechanisms and automation on behalf of our customers.
Specific security knowledge is not required.
The candidate should be a thought leader on the team who is focused on building, delivery, scaling solutions, and mentoring others.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success.
AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Key job responsibilities Advocate for the proper use of AI/ML for the team.
Help guide, teach, and influence others about AI/ML.
Partner with multiple business lines of GSS to understand security use cases and identify appropriate AI/ML opportunities.
Design and execute experiments and proofs-of-concept in AI/ML models to determine the feasibility and fit of AI/ML solutions.
Collaborate with other science teams at Amazon to consistently iterate and improve our AI/ML solutions.
Implement AI/ML models that meet or exceed business requirements for performance and responsibility.
Work with our software engineering teams to help them deliver scalable, maintainable AI/ML-based solutions.
Contribute to GSS culture and activities for building a brighter future for humanity.
A day in the lifeYour day (or week) is a mix of meeting with product and service owners in GSS, sharing information and guidance, and doing hands-on modeling.
In the morning, you meet with one of the product teams to understand their user stories and identify the right opportunities for AI/ML.
After your meeting this morning about the experimental results, you have two more variations to try before a final decision can be made with the product team.
Alternatively, you might pick up where you left off tuning your model for a different product that's further along.
Your accuracy and recall meet the thresholds the product team thinks customers will expect, but you think you can get a few percentage point improvement after talking with some data science colleagues in our Professional Services team last week.
Before you close things down for the day, you do a quick check of your on-line messages to see if anything urgent arose while you were head-down on the ML work - but there's nothing there that can't wait until tomorrow.
Diverse ExperiencesAWS values diverse experiences.
Even if you do not meet all of the 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.
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.
Inclusive Team CultureHere 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.
Mentorship & 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.
Work/Life BalanceWe 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.
Hybrid WorkWe value innovation and recognize this sometimes requires uninterrupted time to focus on a build.
We also value in-person collaboration and time spent face-to-face.
Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.
S.
Amazon offices.
About the teamThe GSS team is seeking a talented data scientist to help lead adoption of AI/ML in our products and services.
GSS is responsible for delivering product-led, people-powered services that help our customers operate their business securely on AWS, and we are accelerating our adoption of AI/ML.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA Herndon, VA, USA Seattle, WA, USABasic qualifications- Bachelor's degree- 4
years of data scientist experience- 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- 5
years previous experience in a ML or data scientist role, with experience of training and deploying ML models- Previous experience working with deep learning frameworks and architectures such as MXNet, TensorFlow, PyTorch, CNN/RNN/LSTM, Autoencoders, TransformersPreferred qualification - 2
years of data visualization using AWS QuickSight, Tableau, R Shiny, etc.
experience- Experience managing data pipelines- Experience as a leader and mentor on a data science team- Phd/MTech/MS in Computer Science, Artificial Intelligence/Machine Learning, Mathematics or Statistics- Experience with AWS AI services (e.
g.
, Amazon Comprehend), ML platforms (Amazon SageMaker), and frameworks (e.
g.
, MXNet, TensorFlow, PyTorch, SparkML, scikit-learn)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.
Our compensation reflects the cost of labor across several US geographic markets.
The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market.
Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
Amazon is a total compensation company.
Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
For more information, please visit https:
//www.
aboutamazon.
com/workplace/employee-benefits.
This position will remain posted until filled.
Applicants should apply via our internal or external career site.
.
Estimated Salary: $20 to $28 per hour based on qualifications.
The candidate will envision, experiment, prototype, and implement AI/ML solutions in our products to meet the needs of our customers.
This is a hands-on role where success is measured by the impact of the AI/ML solutions that meet our customer needs.
The GSS team leverages the expertise and ingenuity of our builders to establish scalable security solutions for both internal and external customers that drive business outcomes.
Our goal of securing the world's workloads and building a brighter future for humanity requires us to focus on reliable delivery of bar raising security outcomes and investment in security mechanisms and automation on behalf of our customers.
Specific security knowledge is not required.
The candidate should be a thought leader on the team who is focused on building, delivery, scaling solutions, and mentoring others.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success.
AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Key job responsibilities Advocate for the proper use of AI/ML for the team.
Help guide, teach, and influence others about AI/ML.
Partner with multiple business lines of GSS to understand security use cases and identify appropriate AI/ML opportunities.
Design and execute experiments and proofs-of-concept in AI/ML models to determine the feasibility and fit of AI/ML solutions.
Collaborate with other science teams at Amazon to consistently iterate and improve our AI/ML solutions.
Implement AI/ML models that meet or exceed business requirements for performance and responsibility.
Work with our software engineering teams to help them deliver scalable, maintainable AI/ML-based solutions.
Contribute to GSS culture and activities for building a brighter future for humanity.
A day in the lifeYour day (or week) is a mix of meeting with product and service owners in GSS, sharing information and guidance, and doing hands-on modeling.
In the morning, you meet with one of the product teams to understand their user stories and identify the right opportunities for AI/ML.
After your meeting this morning about the experimental results, you have two more variations to try before a final decision can be made with the product team.
Alternatively, you might pick up where you left off tuning your model for a different product that's further along.
Your accuracy and recall meet the thresholds the product team thinks customers will expect, but you think you can get a few percentage point improvement after talking with some data science colleagues in our Professional Services team last week.
Before you close things down for the day, you do a quick check of your on-line messages to see if anything urgent arose while you were head-down on the ML work - but there's nothing there that can't wait until tomorrow.
Diverse ExperiencesAWS values diverse experiences.
Even if you do not meet all of the 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.
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.
Inclusive Team CultureHere 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.
Mentorship & 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.
Work/Life BalanceWe 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.
Hybrid WorkWe value innovation and recognize this sometimes requires uninterrupted time to focus on a build.
We also value in-person collaboration and time spent face-to-face.
Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.
S.
Amazon offices.
About the teamThe GSS team is seeking a talented data scientist to help lead adoption of AI/ML in our products and services.
GSS is responsible for delivering product-led, people-powered services that help our customers operate their business securely on AWS, and we are accelerating our adoption of AI/ML.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA Herndon, VA, USA Seattle, WA, USABasic qualifications- Bachelor's degree- 4
years of data scientist experience- 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- 5
years previous experience in a ML or data scientist role, with experience of training and deploying ML models- Previous experience working with deep learning frameworks and architectures such as MXNet, TensorFlow, PyTorch, CNN/RNN/LSTM, Autoencoders, TransformersPreferred qualification - 2
years of data visualization using AWS QuickSight, Tableau, R Shiny, etc.
experience- Experience managing data pipelines- Experience as a leader and mentor on a data science team- Phd/MTech/MS in Computer Science, Artificial Intelligence/Machine Learning, Mathematics or Statistics- Experience with AWS AI services (e.
g.
, Amazon Comprehend), ML platforms (Amazon SageMaker), and frameworks (e.
g.
, MXNet, TensorFlow, PyTorch, SparkML, scikit-learn)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.
Our compensation reflects the cost of labor across several US geographic markets.
The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market.
Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
Amazon is a total compensation company.
Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
For more information, please visit https:
//www.
aboutamazon.
com/workplace/employee-benefits.
This position will remain posted until filled.
Applicants should apply via our internal or external career site.
.
Estimated Salary: $20 to $28 per hour based on qualifications.
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