1

Afternoon Python Financial Jobs (NOW HIRING)

Sr. Software Engineer, AI

Chicago, IL · On-site

$126K - $166K/yr

... their financial destiny. How do we do it? We provide cutting-edge products and services that ... Design and build multi-step agentic workflows in Python and TypeScript - planning loops, tool ...

... afternoon. Key Responsibilities: Training & Development -- The Core of This Role * Conduct one-on ... Lead department-level AI training sessions -- Sales, Construction, Finance, Land, HR, Marketing and ...

New

next page

Showing results 1-20

Afternoon Python Financial information

See salary details

$13

$58

$86

How much do afternoon python financial jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for afternoon python financial in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.
What cities are hiring for Afternoon Python Financial jobs? Cities with the most Afternoon Python Financial job openings:
What are the most commonly searched types of Python Financial jobs? The most popular types of Python Financial jobs are:
What states have the most Afternoon Python Financial jobs? States with the most job openings for Afternoon Python Financial jobs include:
Sr. Data Scientist , Companion Product & Servi (ComPAS)

Sr. Data Scientist , Companion Product & Servi (ComPAS)

Amazon

Seattle, WA • On-site

Full-time

Posted 4 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,891 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

ComPAS Business Insights sits at the intersection of pricing, marketing, and consumer science for Amazon's Companion Products & Services portfolio; spanning Accessories, Pre-Owned Business (POB), and Trade-In (TI). AI is fundamentally changing how we solve these problems. As a Sr.

Data Scientist, you will drive that transformation: building advanced ML models and AI-powered tools that automate decision science at scale, turning complex pricing, targeting, and segmentation challenges into intelligent, self-improving systems.
You will partner with product, marketing, finance, and engineering leaders to translate ambiguous problems into production-ready ML systems and AI-powered tools. Your work will span pricing science, consumer behavior analysis, marketing targeting, propensity score development, and customer segmentation - always with an eye toward how generative AI and foundation models can accelerate, scale, or reimagine the solution.
Key job responsibilities
Key Job Responsibilities
Own the full lifecycle of model development - from problem framing and exploratory analysis through feature engineering, model design, deployment, and continuous improvement.
Oversees the development of pricing science models, including price elasticity estimation, promotional effectiveness measurement, and optimal pricing recommendations across Accessories, POB, and TI product lines.
Build and refine propensity models and customer segmentation frameworks that enable precision marketing targeting and personalized customer engagement.
Conduct consumer behavior analysis to uncover purchase patterns, cross-sell opportunities, and drivers of performance across the ComPAS portfolio.
Leverage generative AI and LLMs (e.g., Amazon Bedrock, foundation models) to build intelligent tools that automate insights generation, scale analytical workflows, and solve problems that were previously intractable.
Identify and execute opportunities to optimize and automate existing analytical and scientific processes -ntransforming manual, repetitive work into scalable AI-powered pipelines.
Design and run rigorous experiments (A/B testing, causal inference, synthetic control) to measure impact and guide strategic decisions on pricing, marketing, and product.
Build data-driven business cases to prioritize science and AI initiatives, demonstrating measurable impact on revenue and customer outcomes.
Contribute to the broader science community by mentoring data scientists and publishing technical work in internal and external forums.
A day in the life
Your mornings start with decision science - framing a pricing or targeting problem, writing Python/SQL to prototype a model, or stress-testing a segmentation approach. Afternoons shift to AI tool-building: experimenting with foundation models, designing automation pipelines, or collaborating with engineers on deployment architecture

Between deep work blocks, you're leading problem-framing sessions with PMs, and business leaders, demoing AI prototypes to stakeholders, or hosting a Lunch & Learn that sparks the next automation idea across the team.
About the team
ComPAS Business Insights is the AI-first data science and analytics team powering Amazon's Companion Products & Services portfolio - Accessories, Pre-Owned Business (POB), and Trade-In (TI). We own the full stack: from production-grade data infrastructure and automated reporting to advanced decision science spanning pricing, consumer behavior, marketing targeting, segmentation, and propensity modeling. We are leveraging AI to build intelligent tools that automate workflows, democratize insights, and put self-service analytics at stakeholders' fingertips

Our mission: turn every pricing, marketing, and customer decision into a science-powered, AI-accelerated outcome.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US