Data Scientist, Professional Services Strategy & Operations, Data Science & Engineering

$125,500 - $212,800/Yr

Amazon - Seattle, WA

Full-time - Mid Level

Seattle, WA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Data Scientist role at Amazon Web Services (AWS) focuses on building data products for the Professional Services (ProServe) - Operations Technology - Data Science and Engineering team. This position involves applying advanced analytical techniques, including machine learning and data modeling, to support enterprise customers in their transition to cloud computing. The role emphasizes collaboration with various stakeholders to develop scalable solutions that drive data insights and business growth.

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 project, including working backwards from customer pain-point, researching project objective, 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 at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports.

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.

Nice-to-haves

• 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.

Benefits

• Flexible work culture
• Mentorship and career growth opportunities
• Diversity and inclusion initiatives
• Work-life balance support
• Hybrid work model options