Data Scientist Ii, Global Accounts Receivable Data - Hyderabad, India - ADCI HYD 13 SEZ

ADCI HYD 13 SEZ

Verified Company

Hyderabad, India

3 weeks ago

Posted by:

Deepika Kaur

beBee Recuiter

Description

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

Amazon's Global Accounts Receivable Data Analytics's (GARDA) science team seeks an outstanding Data Scientist with the technical expertise and business intuition to invent the future of Accounts Receivable at Amazon.

As a key member of the science team, the Data Scientist will own high-visibility analyses, methodology, and algorithms in the Order-to-Cash (O2C) lifecycle to drive free cash flow improvements for Amazon Finance Operations.

This is a unique opportunity in a growing data science and economics team with a charter to optimize operations and planning with complex trade-offs between customer experience, credit risks, cash flow, and operational efficiencies.

Key job responsibilities

The Data Scientist's responsibilities include, but are not limited to the following points:

Extract and analyze large amounts of data from Order-to-Cash processes and associated business functions.
Adapt statistical and machine learning methodologies for Finance Operations by developing and testing models, running computational experiments, and finetuning model parameters.
Use computational methods to identify relationships between business data and outcomes, define outliers and anomalies, and justify those outcomes to business customers.
Communicate verbally and in writing to business customers with various levels of technical knowledge, educate stakeholders on our research and data science practice, and deliver actionable insights and recommendations
Develop code to analyze data (SQL, PySpark, Scala, etc.) and build statistical and machine learning models and algorithms (Python, R, Scala, etc.).
Collaborate with business stakeholders and product managers to innovate on behalf of customers leveraging data science methodologies, and partner with engineers and scientists to design, develop, and scale machine learning models

A day in the life

As a successful data scientist in GARDA's Science team, you will dive deep on data from across Amazon's numerous businesses, extract new assets, drive investigations and algorithm development, and interface with technical and non-technical customers.

You will leverage your data science expertise and communication skills to pivot between delivering science solutions, translating knowledge of financial and operational processes into models, and communicating insights and recommendations to audiences of varying levels of technical sophistication in support of specific business questions, root cause analysis, planning, and innovation for the future.

The role will work in a genuinely global environment, across various functional teams; with daily interaction across India, US, and Europe.

About the team

Global Accounts Receivable is in charge of all AR processes across Amazon's businesses and geographies. Global AR, Data Analytics (GARDA) supports all decisions in AR.

GARDA's mission is to drive a world class Order-to-Cash cycle by providing timely data, insights, and predictions to our leadership and operations teams.

In close cooperation with our stakeholders, we agree and build uniform metrics; use data from a 'single source of truth'; provide automated, self-service, standard reporting; and build predictive analytics.

Our topmost ambition is to actively contribute to the improvement of Amazon's Free Cash Flow by value-adding analytics. Our success is built on users' trust in our data and the reliability of our analytics tools.

GARDA's data scientists and economists further that mission with rigorous statistical, econometric, and ML models to compliment reporting and analysis developed by GARDA's analytical, BI, and Finance professionals.