Description

　　Amazon Selling Partner Services (SPS) team's mission is to make Amazon the safest and most trusted place worldwide to transact online. Amazon runs one of the most dynamic e-commerce marketplaces in the world, with nearly 2 million sellers worldwide selling hundreds of millions of items in ten countries. SPS safeguards every financial transaction across all Amazon sites. As such, SPS designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon.com. SPS organization is looking for a Data Scientist for its Forecasting and Planning Research team. The team is being grown to provide insights about its SPS planning and provide analytical solutions to help drive operational efficiencies, uncover the hidden risks and trends, reduce investigation errors and bad debt, improve customer experience and predict & recommend the optimizations for future state of SPS operations.

　　As a Data Scientist, you will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. You will need to collaborate effectively with internal stakeholders and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidate should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, the candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business.

　　Key job responsibilities

　　Use machine learning techniques to forecast SPS investigations for improved long term and short term capacity planning.

　　Employ the appropriate algorithms to discover patterns of risks, abuse and help reduce bad debt.

　　Design experiments, test hypotheses, and build actionable models to optimize SPS operations.

　　Solve analytical problems, and effectively communicate methodologies and results.

　　Build predictive models to forecast risks for product launches and operations and help predict workflow and capacity requirements for SPS operations.

　　Draw inferences and conclusions, and create dashboards and visualizations of processed data, identify trends, anomalies.

　　Work closely with internal stakeholders such as business teams, engineering teams, and partner teams and align them with respect to your focus area

　　About the team

　　Selling Partner Services (SPS) provides services and solutions aimed at protecting our customers from fraud, counterfeit, and abuse as well as empowering, providing world‐class support, and building loyalty with Amazon’s millions of selling partners.

　　Forecasting & Planning Research (FPR) team in SPS is responsible for estimating the potential future risk on the Amazon platform and its stores using state of art machine learning algorithms and is responsible for translating those estimates into the investigator headcount requirement in each country. The team consists of Data Scientists, Business Intelligence Engineers, Business Analysts and Program Managers.

　　We are open to hiring candidates to work out of one of the following locations:

　　Bangalore, KA, IND

　　Basic Qualifications

　　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

　　Preferred Qualifications

　　Experience in Python, Perl, or another scripting language

　　Experience in a ML or data scientist role with a large technology company