Applied Scientist, Chronicle

Job summary
At Amazon, we strive every day to be Earth’s most customer centric company and data is critical to everything we do, from understanding product profitability to predicting what products to recommend to customers. The Chronicle team provides trustworthy data and insights to Amazonians to help them drive the flywheel. We are looking for an Applied Scientist with 3+ years experience in solving complex problems using machine learning and data science.

As an Applied scientist in Chronicle, you will provide machine learning expertise, work closely with scientists, engineers, and business partners, to build an anomaly detection service to protect business data quality. You will build various data and machine learning models (statistical modeling, time series /non time series forecasting and predictive modeling, optimization, classification, etc.) that help us innovate different ways to enhance analytics. You will need to be entrepreneurial, wear many hats, and work in a highly collaborative environment. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality. Responsibilities include:


Key job responsibilities
1) Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Build statistical models, time series or other predictive/forecasting models, and anomaly detection models for various business problems.
2) Create experiments and prototype implementations of new machine learning algorithms and prediction techniques
3) Collaborate with scientists, engineers, product managers, and stockholders to design and implement software solutions for science problems
4) Use machine learning best practices to ensure a high standard of quality for all of the team deliverables

Basic Qualifications

· M.S. in Applied Statistics, Economics, Industrial Engineering, Operational Research, Computer Science, Machine Learning, or a related quantitative field
· 3+ years of hands-on experience in predictive modeling and analysis, such as time series, forecasting, and statistical modeling.
· 2+ years hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
· 1+ years professional experience in software development
· Working knowledge of web-scale data processing (e.g., Hadoop, Spark).
· Proficiency in model development, model validation and model implementation for large-scale applications
· Ability to convey mathematical results to non-science stakeholders
Strength in clarifying and formalizing complex problems
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

Preferred Qualifications

· Ph.D. in Applied Statistics, Economics, Industrial Engineering, Operational Research, Computer Science, Machine Learning, or a related quantitative field
· 5+ years of practical experience applying ML to solve complex problems in an applied environment
· Significant peer-reviewed scientific contributions in premier journals and conferences.
· Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
· Experience with defining research and development practices in an applied environment



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