Amazonian Experience and Technology (AET) team seeks a data scientist with strong analytical and communication skills to support our goal of becoming the most scientific HR organization in the world. The team is responsible for developing scientific solutions to increase the efficiency and quality of services provided to Amazon’s growing workforce. This includes identifying anomalies in experience metrics, analyzing the causal impact of new events and policies on our services, and building automated solutions using state of the art statistical and machine learning techniques. As part of this team, you will work with Applied Scientists, Economists, and Engineers to constantly innovate on behalf of our employees.
We are looking for motivated data scientists with strong analytical skills who desire to work at the intersection of economics, machine learning and operations research. As a Data Scientist I, Risk Mining, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and improve employee experiences.
You will solve complex problems and partner with other scientists and stakeholders to design the next generation of algorithms to drive the optimization of Amazon’s Employee Services. The candidate should be able to apply a breadth of tools, data sources, and Data Science techniques to answer a wide range of business questions and proactively present new insights in concise and effective manner.
The candidate should be an effective communicator capable of driving issues to resolution with guidance and communicating insights to the team.
Key job responsibilities
* Analyze data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through Data Science
* Build Machine Learning and/or statistical models that detect for trends and anomalies and track impact over time
* Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping
* Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams
* Develop efficient data querying infrastructure for both offline and online use cases
* Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes
* Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use.
* Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations
About the team
Experience Science leverages statistical methods and machine learning technologies to automatically identify employee experience defects at scale. As an employee experience research team, we seek opportunities to build scalable research mechanisms, products and insights to make it effortless for our stakeholders to identify process defects and improve the employee experience.
· Bachelor's Degree
· 2+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· Bachelor’s degree in Statistics, Operational Research, Machine Learning, Computer Science, Economics, a related quantitative field, or equivalent industry experience
· Experience with machine learning, statistical analysis, data mining, and analytics technique
· 3+ years hands-on experience programming in Python, R, or other data analysis and scripting languages
· Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL)Basic knowledge of SQL
Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data
· Experience with AWS services including S3, Redshift, EMR and Kinesis.
· Ability to work independently and problem solve with little to no direction.
· Impeccable customer service focus with a demonstrated desire to exceed expectations.
· Attention to detail; you prioritize multiple tasks simultaneously without sacrificing the ability to dive deep.
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.