Applied Scientist, Marketplace Intelligence, Sponsored Products and Brands

Amazon; Seattle (WA); On-site; USD 136,000 - 224,000; Full time

Job summary

An established industry player is seeking a talented Applied Scientist to join their innovative team focused on developing cutting-edge performance advertising products. In this dynamic role, you will tackle complex machine learning challenges, driving the optimization of ad placements and enhancing the shopping experience for millions. You will have the opportunity to lead projects that leverage big data analytics and deep learning techniques while collaborating with a passionate team. This is your chance to make a significant impact in a fast-paced environment that values creativity and experimentation. If you are ready to embrace this exciting challenge, we want to hear from you!

Qualifications

• 3+ years of experience in building models for business applications.
• Experience in programming languages like Java, C++, and Python.

Responsibilities

• Solve challenging science and business problems balancing interests of advertisers and shoppers.
• Drive end-to-end Machine Learning projects with high ambiguity and scale.

Skills

Machine Learning

Data Mining

Algorithms

Statistical Algorithms

Programming in Java

Programming in C++

Programming in Python

Numerical Optimization

Parallel Computing

Distributed Computing

Education

PhD in Computer Science

Master's degree in Computer Science

Tools

MxNet

TensorFlow

Job description

Applied Scientist, Marketplace Intelligence, Sponsored Products and Brands

Job ID: 2928501 | Amazon.com Services LLC - A57

Calling all inventors to work on exciting new opportunities in Sponsored Products. Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. Sponsored Products (SP) helps merchants, retail vendors, and brand owners grow incremental sales of their products sold on Amazon through native advertising. SP achieves this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. We are a highly motivated, collaborative and fun-loving group with an entrepreneurial spirit and bias for action.

You will join a newly-founded team with a broad mandate to experiment and innovate, with a focus on driving growth of sponsored products ad experiences across Amazon stores worldwide. This broad charter gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers worldwide while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation.

Key job responsibilities

1. Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon.
2. Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
3. Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.
4. Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them.
5. Research new and innovative machine learning approaches.
6. Recruit Scientists to the team and provide mentorship.

BASIC QUALIFICATIONS

1. 3+ years of building models for business application experience.
2. PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
3. Experience programming in Java, C++, Python or related language.
4. 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

1. Experience in professional software development.
2. 3+ years of solving business problems through machine learning, data mining and statistical algorithms experience.
3. Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
4. Experience implementing algorithms using both toolkits and self-developed code.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit this link for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit this link. This position will remain posted until filled. Applicants should apply via our internal or external career site.