Applied Scientist II, Celerity

4 weeks ago

Gurugram, India ADCI - Haryana Full time
Are you looking for an opportunity to build a highly available, large scale, enterprise-wide software solution? Does it excite you to find patterns and build generic, composable software solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Amazon Finance Automation Receivables Technology team.
At FinAuto Receivables Tech, we're committed to delivering exceptional service and efficiency for our valued customers, Amazon, and Global Accounts Receivable (GAR). Our Celerity team is at the forefront of this mission, dedicated to securing customer communications, automating collections tasks, and gathering invaluable Amazon Customer insights.
One of our flagship initiatives, the Zero Touch program, is transforming the way we handle customer communications. In the dynamic world of Account Receivables, we receive over 3.5 million emails annually, and our analysts spend countless hours processing these inquiries manually. However, we're reimagining this process with cutting-edge automation.
Imagine a world where your inquiries are addressed instantly, without the need for manual intervention. That's the vision of our Zero Touch Response (ZTR) program. By harnessing the power of machine learning and advanced workflows, we aim to automate the processing of inbound emails, significantly improving analyst productivity and reducing response times from 120 hours to an astounding 6 hours.
Our innovative solution understands the intent behind each email, leveraging classification models to create intelligent workflows that gather the necessary information and generate tailored responses to your queries. With a modular design, we can effortlessly scale to handle multiple email intents without additional effort.
Moreover, our multilingual capabilities ensure that we can serve customers across diverse marketplaces, breaking down language barriers and providing a seamless experience for all.
Join us on this exciting journey as we redefine customer service with cutting-edge technology. You will lead the ZTR two-pizza team, including a dedicated science team, to collaborate and drive innovation forward.

Key job responsibilities
Applied Scientist should have deep knowledge in the domain of science expertise. They are proficient with state-of-the-art scientific approaches, as well as emerging technologies coming from the research community, which you can fluently communicate to teammates and partners. They should be able to identify existing and future customers’ and business needs or pain points at the project level. They should author or co-author articles for internal or external peer-reviewed venues that validate the novelty of your work.
The components they develop are at least at the same level as those developed by an SDE I and are directly integrated in production, or directly support large systems, applications, product, or services. You are capable of making progress semi-autonomously, with only occasional guidance.
They contribute by participating in tactical and strategic planning such as team goals, priorities and roadmaps. You identify problems and propose solutions for the customer.

About the team
The FinAuto Receivables Tech team strives to consistently evolve and anticipate emerging business needs that drive scale and efficiency for customers, Amazon and Global Accounts Receivable (GAR). The Celerity team is a part of the FinAuto Receivables tech team, charted to secure customer communications, automate collections tasks, and provide Amazon customer insights. One of the Celerity team charters, Zero touch Response, the team will build a solution to automate inbound email processing and respond to customer within SLAs.

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

Gurugram, HR, IND

BASIC QUALIFICATIONS

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

PREFERRED QUALIFICATIONS

- Experience using Unix/Linux
- Experience in professional software development
- Have publications at top-tier peer-reviewed conferences or journals

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