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Data Scientist II, Amazon Currency Convertor

Amazon.com Inc

  • Seattle, WA
  • 30+ days ago

    Highlights

    Demonstrate thorough technical knowledge Fine Tuning of Amazon LLMs to handle large blocks of text, using Generative AI to solve for summarization tasks and prevent catastrophic forgetting, feature engineering of massive datasets, Be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. As a Data Scientist in this team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the Amazon currency convertor business team through a combination of Gen AI, LLM and other machine learning techniques for text analytics, segmentation and prediction.

    Numbers & Facts

    LocationSeattle, WA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    How to use the world's richest collection of e-commerce data to improve payments experience for our customers? Amazon Payments Data Science team seeks a Data Scientist for building analytical solutions that will address increasingly complex business questions in the Amazon Currency convertor space.

    Amazon.com has a culture of data-driven decision-making and demands insights that are timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities.

    As a Data Scientist in this team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the Amazon currency convertor business team through a combination of Gen AI, LLM and other machine learning techniques for text analytics, segmentation and prediction. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

    Key job responsibilities

    • Understand the applications of causal inference models on real datasets, including assessment of marketing campaigns, online experiments, uplift analysis etc
    • Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management
    • Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus are
    • Innovate by adapting new modeling techniques and procedures
    • Effective exploratory data analysis, and model building using industry standard regression and classification techniques such as Random Forest, XGBoost package, Keras framework
    • Demonstrate thorough technical knowledge Fine Tuning of Amazon LLMs to handle large blocks of text, using Generative AI to solve for summarization tasks and prevent catastrophic forgetting, feature engineering of massive datasets,
    • Be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
    • Have exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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