Amazon
Sr Data Scientist, AWS Commerce Platform Monetization
Amazon, Herndon, Virginia, United States, 22070
Sr Data Scientist, AWS Commerce Platform Monetization
As a Senior Data Scientist on the team, you will lead building data science solutions end-to-end and deliver independently on ambiguous and large-scale problems. You will leverage your statistical and machine learning knowledge to address specific business problems. You will retrieve, understand, analyze, and present critical data and insights and communicate (verbal and written) to your partner engineers, scientists, product managers, and leadership to identify business opportunities, support decision making, and drive product innovations. Your primary focus as a Senior Data Scientist will be to utilize your technical acumen to address emerging customer needs, predict potential issues, and drive transformative innovations. Drawing from a deep understanding of complex systems and leveraging advanced analytics and machine learning models, you'll shape AWS's proactive approach to defining customer experiences. Collaborating with cross-functional teams, you'll ensure a unified understanding of customer needs and drive improvements in service delivery. Utilizing your expertise in data science, you'll independently solve complex problems and drive automation solutions to streamline processes. Additionally, you'll contribute to AWS's proactive and reactive measures to resolve customer problems, including customer journey mapping and agile issue resolution by utilizing advanced analytics and machine learning. By implementing these initiatives, you'll significantly enhance AWS's ability to capture customer feedback, address issues proactively, and deliver superior customer experiences, strengthening our competitiveness in the cloud computing landscape. Key job responsibilities Technical Leadership:
Lead the application of data science methodologies to solve complex problems and enhance services and features within the team's domain. Provide technical guidance and solutions with minimal supervision, utilizing your expertise to drive improvements. Shape and influence the business strategy of the team and related teams through data-driven insights. Deliver high-quality results with limited guidance, ensuring alignment with broader business goals. Advanced Analytics and Machine Learning:
Apply advanced analytics, machine learning, and AI techniques to predict potential customer issues and improve customer experiences. Collaborate with cross-functional teams (e.g., Billing Science, CP tech teams, UX researchers) to design and implement holistic solutions. Investigate and implement new methods independently, advocating for necessary measurements and metadata. Customer Focus:
Collaborate closely with customers and cross-functional teams to understand their needs and align technical decisions with business objectives. Lead discussions on design, scoping, and prioritization, proposing data-driven solutions to address customer pain points. Process Optimization and Automation:
Drive the optimization and automation of team processes to achieve organizational goals. Lead implementation reviews and advocate for best practices in automation solutions to simplify workflows and enhance system reliability. Innovation and Problem Solving:
Identify blind spots in current metrics and propose new mechanisms for capturing and analyzing customer feedback. Address root causes of recurring customer issues, ensuring that solutions are comprehensive and effective. Mentorship and Development:
Mentor and develop both junior and senior team members, enhancing their skills in advanced analytics and machine learning. Promote awareness of new data science techniques and their potential applications. Review and provide feedback on the work of other team members to ensure high-quality outputs. About the team AWS Monetization is the incubator and enabler for business model innovation at speed supporting billions in revenue per year and 300+ services from EC2 to ProServe across 7 continents. We support an increasing number of largest enterprise customers around the world as AWS continues to add regions, local legal entities, payment options, and support for complex enterprise financial structures. We are developing cutting-edge technologies and processes to accommodate AWS’s rapid growth. Our team is innovating the complex systems that currently sit on a suite of streamlined solutions that allow us to communicate and offer products to our customers to enhance their experience. As we scale our services, we continue to expand our presence globally to support the AWS Commerce Platform by rapidly deploying pricing models that help AWS to earn customer’s business. We own contract advisory, customer onboarding, invoice creation, invoice distribution, payment collection, and customer success in the AWS contract to cash process. We delight our customers through accurate, compliant billing and payment experience. Our accuracy and timeliness directly impact the cash flow that determines the health of the AWS business, and facilitates cash flow by shortening the time from order to billing/payments. About AWS Diverse Experiences:
AWS 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. 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 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. Mentorship & 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. 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. Minimum Requirements: 7+ years of data science or relevant experience. 7+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience. Proven experience in a similar role, with a focus on customer insights, data analysis, automation, and communication. Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences). Experience using data and metrics to drive improvements. Experience working cross-functionally with technical and non-technical teams. Strong writing skills for creating high-quality documentation. Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field. Experience with statistical models, e.g. multinomial logistic regression. Experience in building automation solutions using AI/machine learning models in coordination with technical teams. Experience in at least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection). 5+ 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. 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 $143,300/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.
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As a Senior Data Scientist on the team, you will lead building data science solutions end-to-end and deliver independently on ambiguous and large-scale problems. You will leverage your statistical and machine learning knowledge to address specific business problems. You will retrieve, understand, analyze, and present critical data and insights and communicate (verbal and written) to your partner engineers, scientists, product managers, and leadership to identify business opportunities, support decision making, and drive product innovations. Your primary focus as a Senior Data Scientist will be to utilize your technical acumen to address emerging customer needs, predict potential issues, and drive transformative innovations. Drawing from a deep understanding of complex systems and leveraging advanced analytics and machine learning models, you'll shape AWS's proactive approach to defining customer experiences. Collaborating with cross-functional teams, you'll ensure a unified understanding of customer needs and drive improvements in service delivery. Utilizing your expertise in data science, you'll independently solve complex problems and drive automation solutions to streamline processes. Additionally, you'll contribute to AWS's proactive and reactive measures to resolve customer problems, including customer journey mapping and agile issue resolution by utilizing advanced analytics and machine learning. By implementing these initiatives, you'll significantly enhance AWS's ability to capture customer feedback, address issues proactively, and deliver superior customer experiences, strengthening our competitiveness in the cloud computing landscape. Key job responsibilities Technical Leadership:
Lead the application of data science methodologies to solve complex problems and enhance services and features within the team's domain. Provide technical guidance and solutions with minimal supervision, utilizing your expertise to drive improvements. Shape and influence the business strategy of the team and related teams through data-driven insights. Deliver high-quality results with limited guidance, ensuring alignment with broader business goals. Advanced Analytics and Machine Learning:
Apply advanced analytics, machine learning, and AI techniques to predict potential customer issues and improve customer experiences. Collaborate with cross-functional teams (e.g., Billing Science, CP tech teams, UX researchers) to design and implement holistic solutions. Investigate and implement new methods independently, advocating for necessary measurements and metadata. Customer Focus:
Collaborate closely with customers and cross-functional teams to understand their needs and align technical decisions with business objectives. Lead discussions on design, scoping, and prioritization, proposing data-driven solutions to address customer pain points. Process Optimization and Automation:
Drive the optimization and automation of team processes to achieve organizational goals. Lead implementation reviews and advocate for best practices in automation solutions to simplify workflows and enhance system reliability. Innovation and Problem Solving:
Identify blind spots in current metrics and propose new mechanisms for capturing and analyzing customer feedback. Address root causes of recurring customer issues, ensuring that solutions are comprehensive and effective. Mentorship and Development:
Mentor and develop both junior and senior team members, enhancing their skills in advanced analytics and machine learning. Promote awareness of new data science techniques and their potential applications. Review and provide feedback on the work of other team members to ensure high-quality outputs. About the team AWS Monetization is the incubator and enabler for business model innovation at speed supporting billions in revenue per year and 300+ services from EC2 to ProServe across 7 continents. We support an increasing number of largest enterprise customers around the world as AWS continues to add regions, local legal entities, payment options, and support for complex enterprise financial structures. We are developing cutting-edge technologies and processes to accommodate AWS’s rapid growth. Our team is innovating the complex systems that currently sit on a suite of streamlined solutions that allow us to communicate and offer products to our customers to enhance their experience. As we scale our services, we continue to expand our presence globally to support the AWS Commerce Platform by rapidly deploying pricing models that help AWS to earn customer’s business. We own contract advisory, customer onboarding, invoice creation, invoice distribution, payment collection, and customer success in the AWS contract to cash process. We delight our customers through accurate, compliant billing and payment experience. Our accuracy and timeliness directly impact the cash flow that determines the health of the AWS business, and facilitates cash flow by shortening the time from order to billing/payments. About AWS Diverse Experiences:
AWS 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. 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 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. Mentorship & 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. 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. Minimum Requirements: 7+ years of data science or relevant experience. 7+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience. Proven experience in a similar role, with a focus on customer insights, data analysis, automation, and communication. Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences). Experience using data and metrics to drive improvements. Experience working cross-functionally with technical and non-technical teams. Strong writing skills for creating high-quality documentation. Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field. Experience with statistical models, e.g. multinomial logistic regression. Experience in building automation solutions using AI/machine learning models in coordination with technical teams. Experience in at least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection). 5+ 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. 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 $143,300/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.
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