Amazon
Data Scientist, Professional Services Strategy & Operations, Data Science & Engi
Amazon, Seattle, Washington, us, 98127
Data Scientist, Professional Services Strategy & Operations, Data Science & Engineering
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? Do you live and breathe algorithms that lead to predictive and prescriptive analytics? 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.Minimum Requirements
2+ 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.Experience applying theoretical models in an applied environment.Experience in Python, Perl, or another scripting language.Experience in a ML or data scientist role with a large technology company.Experience with AWS technologies like Redshift, S3, EC2, SageMaker, Glue, Bedrock.Experience using ML libraries, such as scikit-learn, caret, mlr, or mllib.Experience with business intelligence and data visualization and reporting tools (e.g. Tableau, QuickSight, etc.).Experience forecasting in sales and/or professional services.Experience writing and presenting complex technical concepts to broad audiences.Ability to manage competing priorities in an ambiguous environment.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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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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? Do you live and breathe algorithms that lead to predictive and prescriptive analytics? 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.Minimum Requirements
2+ 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.Experience applying theoretical models in an applied environment.Experience in Python, Perl, or another scripting language.Experience in a ML or data scientist role with a large technology company.Experience with AWS technologies like Redshift, S3, EC2, SageMaker, Glue, Bedrock.Experience using ML libraries, such as scikit-learn, caret, mlr, or mllib.Experience with business intelligence and data visualization and reporting tools (e.g. Tableau, QuickSight, etc.).Experience forecasting in sales and/or professional services.Experience writing and presenting complex technical concepts to broad audiences.Ability to manage competing priorities in an ambiguous environment.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.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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