decision scientist, operations research Jobs in Seattle

decision scientist, operations research

data scientist

Starbucks

<div>
 
 Now Brewing &ndash; Decision Scientist, Operations Research! #tobeapartner
 
 
 
 From the beginning, Starbucks set out to be a different kind of company. One that not only
 
 
 celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
 
 
 As a Decision Scientist on the Global Supply Chain (GSC) Network Optimization team, you will serve in an applied technical role leading analytical development and optimization efforts for our supply chain network. You will design, model and optimize end-to-end supply chain topology solutions encompassing manufacturing, sourcing, transportation, warehousing, and final mile delivery inclusive of within-coffeehouse impacts to drive resilience, cost efficiency, and service. Working cross-functionally with data engineers, data scientists, business experts, and external vendors, you will play a critical role integrating mathematical modeling and real-world operational decision-making to deliver results for our business, partners and customers.
 
 
 
 As a decision scientist, you will&hellip;
 
 
 
 <ul>
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 Formulate, develop, and deploy optimization, simulation, and mathematical models addressing:
 </li>
 <ul>
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 Distribution network topology, design and long-range planning to achieve cost and service objectives
 </li>
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 Multiechelon inventory flow
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 Transportation routing, scheduling and mode optimization
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 Final mile replenishment to our coffeehouses
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 </ul>
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 Evaluate unstructured questions from business teams and translate into data problems
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 Apply statistical knowledge to create optimization models &amp; predictive analyses
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 Utilize systems thinking approach to conceive, plan, and build new data products
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 Drive adoption of data products and insights across business teams by visualizing results and crafting effective communications to share discoveries
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 Lead data science solutions as an embedded technical expert from beginning to end
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 Build relationships with a wide-range of business partners and establish yourself and the team as subject matter experts in supply chain analytics
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 Ability to work independently and through ambiguous situations to build relevant analytic solutions using quantitative approaches
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 Strong presentation skills to be able to share insights and recommendations at a senior leadership level and also more detailed technical reviews with the analytics community
 
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 </ul>
 
 We&rsquo;d Love To Hear From People With
 
 
 
 <ul>
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 MS+ with concentration in quantitative discipline &ndash; Operations Research, Stats, Math, Comp Sci, Engineering, Econ, or similar discipline
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 Strong background working with predictive and statistical modeling, machine learning, optimization and strong expertise in all phases of the modeling pipeline
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 Experience building complex data sets from multiple data sources, both internally and externally
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 Strong SQL, database and ETL skills required including cleaning and managing data
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 Advanced competency and expertise in Python, R or some combination
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 Experience with integer programming, local search heuristics, and related OR tools (e.g. Gurobi, CPLEX, XPRESS)
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 Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities
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 Ability to educate others on statistical / optimization modeling methods
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 Self-starter, attention to details and results orientated, able to work under minimal guidance
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 Proficient in communicating effectively with both technical and nontechnical stakeholders
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 Experience on Cloud platforms such as Azure, AWS, preferred
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 Experience with multi-echelon network design and inventory optimization, preferred
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 Experience developing and fitting machine learning models, preferred
 
 
 </li>
 </ul>
 As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor&rsquo;s degree through Arizona State University&rsquo;s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com.
 
 
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 If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.
 
 
 </li>
 </ul>
 The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
 
 
 We believe we do our best work when we're together, which is why we're onsite four days a week.
 
 
 
 Join us and inspire with every cup. Apply today!
 
 
 
 Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
 
 
 Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.
 
 
 Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation or 1(888) 611-2258.
</div>

decision scientist, Operations Research

TikTok

Technology
 
Senior Machine Learning Engineer, Shop Ads - USDS
 
Location
 :
 
Seattle
 
Employment Type
 :
 
Regular
 
Job Code
 :
 
A251554A
 
Responsibilities
 
About the team
 The TikTok USDS Shop Ads team is dedicated to blending advertiser focus with technical expertise. Our mission is to enhance shop ads—both open-loop and closed-loop—to establish TikTok US as an essential growth engine for businesses of all sizes and a top destination for consumers to discover and buy products, content, and services. We are crucial to driving TikTok's ad revenue and are committed to developing the next-generation shop ad solutions for the platform.
 
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
 
Responsibilities: 
<ul>
<li>Build highly scalable machine learning systems and state-of-the-art machine learning models to improve ad ranking quality and optimize advertisers' marketing strategies. Examples include but are not limited to click through rate prediction, conversion rate prediction, intelligent format selection and user journey optimization.</li>
<li>Explore, develop and experiment with new features to improve model accuracy.</li>
<li>Understand ads platform objectives and take full advantage of modern machine learning to improve ads relevance, quality, and quantity delivered to end-users.</li>
<li>Collaborate with Global counterpart, Product Managers, Designers, and other disciplines to explore the next generation of shopping experiences on TikTok.</li>
</ul>
Qualifications
 
Minimum Qualifications: 
<ul>
<li>Highly self-motivated to drive business growth and foster technical advancement.</li>
<li>Proficient in using SQL and Python and experience with data manipulation</li>
<li>Experience with big data processing frameworks (e.g., Hadoop, Spark) and distributed computing for efficient data mining on large-scale datasets.</li>
<li>Solid understanding of machine/deep learning concepts and techniques, including feature engineering, model evaluation, and optimization.</li>
<li>Strong analytical and problem-solving skills, with a demonstrated ability to handle and derive insights from complex and unstructured datasets.</li>
</ul>
Preferred Qualifications: 
<ul>
<li>Master's or advanced degree in Computer Science, Data Science, Statistics, or a related field.</li>
<li>5+ years experience as a Machine Learning Engineer, Data Scientist, and experience in causal machine learning is preferred</li>
<li>Work experience in user growth, marketing algorithms, recommendation algorithms, advertisement algorithms or related fields is preferred.</li>
<li>Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders.</li>
</ul>
Job Information
 
【For Pay Transparency】Compensation Description (Annually)
 
The base salary range for this position in the selected city is $177688 - $341734 annually.
 
​
 
Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
 
​
 
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
 
​
 
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
 
​
 
For Los Angeles County (unincorporated) Candidates: 
​
 
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
 
​
 
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
 
​
 
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
 
​
 
3. Exercising sound judgment.
 
​
 
About USDS
 
TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. U.S. Data Security (“USDS”) is a subsidiary of TikTok in the U.S. This new, security-first division was created to bring heightened focus and governance to our data protection policies and content assurance protocols to keep U.S. users safe. Our focus is on providing oversight and protection of the TikTok platform and U.S. user data, so millions of Americans can continue turning to TikTok to learn something new, earn a living, express themselves creatively, or be entertained. The teams within USDS that deliver on this commitment daily span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions and more.
 
​
 
Why Join Us
 
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
 
​
 
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
 
​
 
​
 
Diversity & Inclusion
 
​
 
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
 
​
 
USDS Reasonable Accommodation
 
USDS is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at
 
https://tinyurl.com/USDS-RA

Senior Machine Learning Engineer, Shop Ads - USDS

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! 
 
Our team owns personalization, guidance and experimentation science and is placed centrally in the organization which owns the Amazon Advertising Console from UX design to components and services. We leverage a breadth of state-of-the-art techniques such as deep learning, reinforcement learning, LLMs, long term causal modeling as well as sophisticated A/B testing to develop personalized experiences with directly quantifiable business and advertiser success outcomes. We are looking for an accomplished machine learning expert to lead the Applied Science strategy for our recommendation creation and recommendation personalziation program.
 
 
In this role, you will work closely with business leaders, stakeholders and cross-functional teams to drive program success through ML-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact for millions of advertisers worldwide and the company using advanced data techniques and applied science methodologies. 
 
Key job responsibilities 
As an Applied Scientist on this team, you will 
 
<ul><li>Serve as the technical leader in Machine Learning, driving collaboration between scientists and engineers, guiding efforts within the team and collaborating with other teams.</li><li>Conduct hands-on analysis and modeling of large-scale data to generate insights that boost ads revenue while maintaining a positive advertiser and shopper experience.</li><li>Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity.</li><li>Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production.</li><li>Run A/B experiments, gather data, and perform statistical analysis to validate your models.</li><li>Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving.</li><li>Explore and research innovative machine learning approaches to push the boundaries of what&rsquo;s possible.</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building models for business application experience</li><li>PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience using Unix/Linux</li><li>Experience in professional software development</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Personalization, DTx Science

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company&rsquo;s Think Big leadership principle to the limits. If you&rsquo;re interested in innovating at scale to address big challenges in the world, this is the team for you.
 
 
Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. 
 
We are seeking a Principal Applied Scientist working on machine learning applications in life sciences. This role combines scientific leadership with hands-on innovation, driving solutions from exploratory research through production-ready solutions deployment, while maintaining high scientific standards. You will work with Amazon's large-scale computing resources to accelerate advances in machine learning applications. 
 
Key job responsibilities 
<ul><li>Lead ML for life science efforts using computational design approaches and ML-based tools.</li><li>Guide teams in applying SOTA ML methods, experimentation design, and modeling approaches.</li><li>Transform complex real world problems into scientific challenges and allocate resources effectively.</li><li>Review requirements, conduct technical architecture reviews, and make informed judgments around technical and business tradeoffs.</li><li>Provide mentorship to Applied Scientists, Research Scientists and Data Scientists while maintaining scientific rigor.</li><li>Collaborate with cross functional teams.</li></ul></div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>Deep expertise in machine learning, with broad knowledge across biology and life science.</li><li>Strong understanding of scientific methodologies and experimental design.</li><li>Ability to develop production-level code and systems.</li><li>Track record of working with cross-functional scientific teams and fostering collaboration.</li><li>10+ years of relevant, broad research experience after a PhD degree in computer science, computational biology or relevant field .</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with deep learning frameworks (PyTorch, TensorFlow).</li><li>Familiarity with high-performance computing environments.</li><li>Experience with ML for science and structural biology tools.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;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 $179,000/year in our lowest geographic market up to $309,400/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Principal Applied Scientist, Amazon Special Projects

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity&mdash;from electronics to groceries to digital content. 
 
The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data&mdash;while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. 
 
Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. 
 
Key job responsibilities 
Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval&mdash;translating ambiguous business challenges into tractable scientific frameworks 
 
Design and implement systems leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale 
 
Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions 
 
Optimize and scale large-language-model inference pipelines, including model compression, parallelization, and workflow orchestration, to support massive-volume LLM workflows with low latency and high reliability. 
 
Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements 
 
Mentor junior scientists and engineers on advanced ML techniques, experimental design, and scientific rigor&mdash;building organizational capability in GenAI and multimodal AI 
 
Represent the team in the broader science community&mdash;publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>4+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;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 $150,400/year in our lowest geographic market up to $260,000/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Senior Applied Scientist

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
About Sponsored Products and Brands:
 
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
 
 
About Our Team:
 
The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products.
 
 
About This Role: 
As a Principal Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer&rsquo;s needs, and translate it into actionable plans for our team of applied scientists and engineers. 
 
This role will play a critical role in elevating the team&rsquo;s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. 
 
<ul><li>Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance.</li><li>Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.
</li><li>Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses.
</li><li>Effectively communicate technical and non-technical ideas with teammates and stakeholders.</li><li>Stay up-to-date with advancements and the latest modeling techniques in the field.</li><li>Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems.</li></ul> 
#GenAI</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD in Computer Science, Statistics or related field.</li><li>10+ years of programming in Java, Python or related language.</li><li>10+ years of applied ML experience in building complex, real-time systems involving AI, ML with successful delivery to customers.</li><li>3+ years in LLMs, model fine tuning and prompt engineering.</li><li>3+ years in digital advertising technology.</li></ul><h2 class="jobSectionHeader"> 
PREFERRED QUALIFICATIONS</h2><ul><li>Demonstrated track record of innovative AI solution development.</li><li>Experience with generative model architectures.</li><li>Research publications or patents in generative AI technologies.</li><li>Experience in Reinforcement Learning from Human Feedback (RLHF), Retrieval-Augmented Generation (RAG) and AI model trade-offs (e.g., model size, latency, cost, and output quality).</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;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 $179,000/year in our lowest geographic market up to $309,400/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Principal Applied Scientist, Sponsored Products and Brands

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is transforming advertising through generative AI technologies. We help millions of customers discover products and engage with brands across Amazon.com and beyond. Our team combines human creativity with artificial intelligence to reinvent the entire advertising lifecycle&mdash;from ad creation and optimization to performance analysis and customer insights. 
 
We develop responsible AI technologies that balance advertiser needs, enhance shopping experiences, and strengthen the marketplace. Our team values innovation and tackles complex challenges that push the boundaries of what's possible with AI. 
 
Join us in shaping the future of advertising. 
 
Key job responsibilities 
This role will redesign how ads create personalized, relevant shopping experiences with customer value at the forefront. Key responsibilities include: 
 
<ul><li>Design and develop solutions using GenAI, deep learning, multi-objective optimization and/or reinforcement learning to transform ad retrieval, auctions, whole-page relevance, and shopping experiences.</li><li>Partner with scientists, engineers, and product managers to build scalable, production-ready science solutions.</li><li>Apply industry advances in GenAI, Large Language Models (LLMs), and related fields to create innovative prototypes and concepts.</li><li>Improve the team's scientific and technical capabilities by implementing algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor junior scientists and engineers to build a high-performing, collaborative team.</li></ul> 
A day in the life 
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. 
 
About the team 
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Demonstrated expertise in Generative AI technologies, including foundation models, LLMs, and model customization for specific business applications</li><li>Hands-on experience building ads ranking, retrieval, recommendation, or personalization systems that operate at web scale</li><li>Technical proficiency in advanced AI approaches such as multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF)</li><li>Track record of designing and implementing online experimentation frameworks, including A/B testing methodologies and performance metrics for advertising or e-commerce</li><li>Proven ability to translate complex technical concepts into clear explanations for diverse audiences, from engineers to executives</li><li>Deep knowledge of computational advertising fundamentals, including auction mechanisms, advertising economics, and advertiser success metrics</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;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 $150,400/year in our lowest geographic market up to $260,000/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Senior Applied Scientist, Sponsored Products and Brands, Off-Search

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