Data Scientist, Amazon

Amazons Consumer Payments organization is seeking a highly quantitative experienced Data Scientist to drive the development of science analytics and insights capabilities. You will succeed in this role if you are an organized self-starter who can learn new technologies quickly and excel in a fast-paced this position you will be a key contributor and sparring partner developing analytics and insights that global executive management teams and business leaders will use to define global strategies and deep dive businesses.
Our team is a brand-new Analytics team offering a unique opportunity to build a new set of analytical experiences from the ground up. You will be part the team that is focused developing analytical solutions for our customers (Product/Marketing/Finance/Operations team). The position is based in India but will interact with global leaders and teams in Europe Japan US and other regions. You should be highly analytical resourceful customer focused team oriented and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced dynamic business environment is strongly preferred.

Key job responsibilities
Working with technical and non-technical stakeholders across every step of science project life cycle.
Design develop implement test forecasting solutions for planning and goal setting exercises across various payment products and programs across CP organization.
Apply statistical and machine learning techniques to extract meaningful trends and insights.
Identifying real-time anomalies and early-detection mechanisms.
Collaborate with Analysts Business Intelligence Engineers and Product Managers to implement algorithms that exploit rich data sets for statistical analysis and machine learning.
Work with product tech teams BIE/DE and build robust and scalable science solutions integration with in house reporting/BI tools using SQL Python and Spark.
Leading training and informational sessions on our science and capabilities.
Write share and present documents summarizing your findings and recommendations to all levels of organization.
Well versed in the relevant literature and have the ability to identify analyze and adapt new state-of-the-art methods as well as beyond to create new problem-solution pairs to build breakthroughs.
Communicate effectively with product/business/tech-teams/other science teams.

- 1 years of data querying languages (e.g. SQL) scripting languages (e.g. Python) or statistical/mathematical software (e.g. R SAS Matlab etc.) experience
- 2 years of data/research scientist statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- 1 years of creating or contributing to mathematical textbooks research papers or educational content experience
- Masters degree in Science Technology Engineering or Mathematics (STEM) or experience working in Science Technology Engineering or Mathematics (STEM)
- Bachelors or Masters degree in computer science engineering or a related technical field
- Experience with data scripting languages (e.g. SQL Python R etc.) or statistical/mathematical software (e.g. R SAS or Matlab)
- Experience using complex modeling and analysis to inform key business decisions
- Experience that includes strong analytical skills attention to detail and effective communication abilities or experience in SQL Server/MySQL
- Experience with big data technologies such as AWS Hadoop Spark Pig Hive etc.
- Can work proactively and independently meet deadlines and deliver on projects and tasks
- Experience troubleshooting and documenting findings or experience driving collaborative projects from conception to delivery

- Ph.D. in Science Technology Engineering or Mathematics (STEM)
- Knowledge of statistical packages and business intelligence tools such as SPSS SAS S-PLUS or R
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience with clustered data processing (e.g. Hadoop Spark Map-reduce and Hive)
- Experience working with or evaluating AI systems
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
- Masters degree or above in a quantitative field such as statistics mathematics data science business analytics economics finance engineering or computer science or PhD
- Knowledge of AWS platforms such as S3 Glue Athena Sagemaker
- Knowledge of software engineering best practices across the development life cycle including agile methodologies coding standards code reviews source management build processes testing and operations
- Experience in complex problem solving and working in a tight schedule environment

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