Amazon
Data Scientist, Professional Services Strategy & Operations, Data Science & Engi
Amazon, Seattle, Washington, us, 98127
Data Scientist, Professional Services Strategy & Operations, Data Science & Engineering
Job ID: 2736091 | Amazon Web Services, Inc.Amazon Web Services (AWS) is seeking an experienced Data Scientist to build data products for the Professional Services (ProServe) - Operations Technology - Data Science and Engineering team. This is a unique opportunity to think big, insist on the highest standards, and invent and simplify the data products to scale and accelerate our enterprise customers' journey to the cloud. The Data Science and Engineering team builds advanced analytical products, including feature engineering, predictive and prescriptive modeling, and generative AI application development for internal customers.Do you have expertise in a range of data science methodologies and a track record of developing machine learning (ML) models to answer business questions at scale? In this role, you will apply scientific principles to business problems, analyzing complex data sets to make rapid decisions for practice development and operations leaders. You will create visualizations and develop models to drive data insights and scale algorithms. In partnership with engineers, analysts, and business owners, you will work backwards from business objectives to drive scalable solutions with statistical and machine learning models. You will be a technical leader influencing the analyses and best practices across multiple teams. Above all, you should be passionate about working with data to answer business questions and drive growth.Key job responsibilities
Demonstrate thorough technical knowledge on feature engineering of large datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models.Work closely with internal stakeholders like the business teams, engineering teams, and partner teams and align them with respect to your focus area.Proficiency in both supervised and unsupervised algorithms to build predictive and prescriptive solutions for AWS Professional Services organization.Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management.Conduct end-to-end AI/ML projects, including working backwards from customer pain-points, researching project objectives, building and evaluating models, and communicating project results to stakeholders.Proficiency with dataset creation and management and passionate about working with huge data sets (training/fine-tuning).Exposure to implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing, and adaptive.About the team
The ProServe Strategy & Operations - Operations Technology team delivers relentless innovation that accelerates smarter decisions for a better Professional Services through technology, automation, and advanced analytics. Our mission is to provide AWS with the right information at the right time to make analytically-informed decisions about business performance and desired outcomes. The team supports AWS Professional Service's mission by ensuring that our data are trusted and secured via business systems and automation technologies to deliver actionable insights that drive business growth and efficiencies.BASIC QUALIFICATIONS
2+ years of data scientist experience3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experienceExperience applying theoretical models in an applied environmentPREFERRED QUALIFICATIONS
Experience in Python, Perl, or another scripting languageExperience in a ML or data scientist role with a large technology companyExperience with AWS technologies like Redshift, S3, EC2, SageMaker, Glue, BedrockExperience using ML libraries, such as scikit-learn, caret, mlr, or mllibExperience with business intelligence and data visualization and reporting tools (e.g. Tableau, QuickSight, etc)Experience forecasting in sales and/or professional servicesExperience writing and presenting complex technical concepts to broad audiencesAbility to manage competing priorities in an ambiguous environmentAmazon 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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Job ID: 2736091 | Amazon Web Services, Inc.Amazon Web Services (AWS) is seeking an experienced Data Scientist to build data products for the Professional Services (ProServe) - Operations Technology - Data Science and Engineering team. This is a unique opportunity to think big, insist on the highest standards, and invent and simplify the data products to scale and accelerate our enterprise customers' journey to the cloud. The Data Science and Engineering team builds advanced analytical products, including feature engineering, predictive and prescriptive modeling, and generative AI application development for internal customers.Do you have expertise in a range of data science methodologies and a track record of developing machine learning (ML) models to answer business questions at scale? In this role, you will apply scientific principles to business problems, analyzing complex data sets to make rapid decisions for practice development and operations leaders. You will create visualizations and develop models to drive data insights and scale algorithms. In partnership with engineers, analysts, and business owners, you will work backwards from business objectives to drive scalable solutions with statistical and machine learning models. You will be a technical leader influencing the analyses and best practices across multiple teams. Above all, you should be passionate about working with data to answer business questions and drive growth.Key job responsibilities
Demonstrate thorough technical knowledge on feature engineering of large datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models.Work closely with internal stakeholders like the business teams, engineering teams, and partner teams and align them with respect to your focus area.Proficiency in both supervised and unsupervised algorithms to build predictive and prescriptive solutions for AWS Professional Services organization.Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management.Conduct end-to-end AI/ML projects, including working backwards from customer pain-points, researching project objectives, building and evaluating models, and communicating project results to stakeholders.Proficiency with dataset creation and management and passionate about working with huge data sets (training/fine-tuning).Exposure to implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing, and adaptive.About the team
The ProServe Strategy & Operations - Operations Technology team delivers relentless innovation that accelerates smarter decisions for a better Professional Services through technology, automation, and advanced analytics. Our mission is to provide AWS with the right information at the right time to make analytically-informed decisions about business performance and desired outcomes. The team supports AWS Professional Service's mission by ensuring that our data are trusted and secured via business systems and automation technologies to deliver actionable insights that drive business growth and efficiencies.BASIC QUALIFICATIONS
2+ years of data scientist experience3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experienceExperience applying theoretical models in an applied environmentPREFERRED QUALIFICATIONS
Experience in Python, Perl, or another scripting languageExperience in a ML or data scientist role with a large technology companyExperience with AWS technologies like Redshift, S3, EC2, SageMaker, Glue, BedrockExperience using ML libraries, such as scikit-learn, caret, mlr, or mllibExperience with business intelligence and data visualization and reporting tools (e.g. Tableau, QuickSight, etc)Experience forecasting in sales and/or professional servicesExperience writing and presenting complex technical concepts to broad audiencesAbility to manage competing priorities in an ambiguous environmentAmazon 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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