Data Scientist II, Global Accounts Receivable, Data Analytics (GARDA) Job Vacancy in ADCI – Karnataka Bengaluru, Karnataka – Updated today

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Company Name : ADCI – Karnataka
Location : Bengaluru, Karnataka
Position :

Job Description : Bachelor’s Degree
3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
2 years working as a Data Scientist
Master’s degree+ in a quantitative field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or Economics.
5+ years’ of industry experience with data querying languages (e.g. SQL), scripting languages (e.g. Python, R), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.).
At least 3 years’ experience articulating business questions and using quantitative modelling and statistical analysis techniques to arrive at a solution using available data.
Experience with Java, C++, R, PL/SQL, Oracle 11g, MS SQL Server and Amazon Web Services: Redshift
Depth and breadth in quantitative knowledge, quantitative modelling, statistical analysis and problem-solving skills.
Demonstrable record of accomplishment of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relations.
Experience with modelling sequential data, statistical forecasting, and time series models.
Experience processing, filtering, and presenting large quantities (billions of rows) of data.

Job summary
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 fine-tuning 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, in a daily interaction with 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.

PhD in a quantitative field
Formal training in Statistics, Economics, Econometrics or similar discipline
Familiarity with business-specific (AR/Accounting) processes
Depth of knowledge in machine learning algorithms
Understanding of Amazon Web Services (AWS) technologies
Experience in supply chain is a plus
Track record of defining science vision and strategy

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