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Data Scientist, AWS Industries

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Amazon

2mo ago

  • Job
    Full-time
    Senior Level
  • Data
    IT & Cybersecurity
  • Miami

AI generated summary

  • You need 5+ years as a data scientist, 3+ years in SQL/Python, machine learning, a quantitative degree, PhD preferred, and experience with deep learning and fine-tuning LLMs, ideally on AWS.
  • You will collaborate with teams on generative AI solutions, engage with customers to understand needs, create best practices and tutorials, and provide feedback to guide product development.

Requirements

  • 5+ 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
  • Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
  • 5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer)
  • Prior experience in training and fine-tuning of Large Language Models (LLMs)
  • Knowledge of AWS platform and tools or equivalent cloud experience

Responsibilities

  • As a Data Scientist, you will
  • Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms and build ML systems to address real-world challenges
  • Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production
  • Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder
  • Provide customer and market feedback to Product and Engineering teams to help define product direction

FAQs

What is the main focus of the Data Scientist role in AWS Industries?

The main focus of the Data Scientist role in AWS Industries is to apply cutting-edge Generative AI algorithms to solve real-world problems and help AWS customers implement bespoke generative AI solutions that create transformational business opportunities.

What types of collaboration can I expect in this role?

In this role, you will collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate generative AI algorithms and build machine learning systems.

Will I interact with customers directly?

Yes, you will interact directly with customers to understand their business challenges, aid in the implementation of generative AI solutions, and deliver various sessions and guidance on adoption patterns.

What are the basic qualifications needed for this position?

The basic qualifications include 5+ years of data scientist experience, 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and statistical/mathematical software, as well as a bachelor's degree in a quantitative field.

Are there any preferred qualifications for this role?

Yes, preferred qualifications include a PhD in a quantitative field, 5+ years of experience in machine learning/statistical modeling, hands-on experience with deep learning models, prior experience with training Large Language Models, and knowledge of the AWS platform.

Is there support for career growth and mentorship?

Yes, AWS emphasizes mentorship and career growth, providing endless knowledge-sharing and resources to help you develop into a well-rounded professional.

Does the company promote diversity and inclusion?

Yes, Amazon is committed to a diverse and inclusive workplace, advocating for a culture that celebrates differences and supports various employee-led affinity groups.

What does the compensation package include?

The compensation package includes a base pay that ranges from $125,500 to $212,800 annually, depending on the geographic market, as well as other forms of compensation such as equity, sign-on payments, and a full range of medical and financial benefits.

What are the work-life balance policies at AWS?

AWS values work-life harmony and strives for flexibility within its working culture, believing that success at work should not come at the expense of personal life.

Are there any specific job safety requirements for this position?

Yes, job duties include adhering to standards of excellence, communicating effectively with colleagues, and following all applicable laws and company policies to ensure a safe working environment.

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Amazon

Retail & Consumer Goods
Industry
10,001+
Employees
1994
Founded Year

Mission & Purpose

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one. Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world. Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind. You'll also hear us say that at Amazon, it's always "Day 1."​ What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.