Sr. Data Scientist, AWS Industries

DESCRIPTION

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting-edge Generative AI algorithms to solve real-world problems with significant impact? The AWS Industries Team helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select, train, and fine-tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost-efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

In this Data Scientist role, you will be capable of using GenAI and other techniques to design, evangelize, implement, and scale cutting-edge solutions for never-before-solved problems.

Key job responsibilities
As a Senior Data Scientist, you will:

1. 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.
2. Interact with customers directly to understand the business problem, aid them in the implementation of generative AI solutions, deliver briefing and deep dive sessions to customers, and guide customers on adoption patterns and paths to production.
3. Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholders.
4. Provide customer and market feedback to Product and Engineering teams to help define product direction.

BASIC QUALIFICATIONS

1. Bachelor’s degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Master’s degree.
2. Experience working as a Data Scientist.
3. Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent).
4. Experience in machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance.
5. Experience applying theoretical models in an applied environment.

PREFERRED QUALIFICATIONS

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

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