aiml - sr backend engineer, data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

988 crisis intervention specialist (overnight)

administrative assistant senior Jobs in Seattle

administrative assistant senior

aiml - sr backend engineer, data and ml innovation Jobs in Seattle

aiml - sr machine learning engineer, data and ml innovation Jobs in Seattle

aws data engineer

data engineer ii , na stores expansion Jobs in Seattle

data engineer ii , na stores expansion

senior data scientist

Amazon

<div>
 
 Description
 
 
 
 Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match!
 
 
 Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience.
 
 
 The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist.
 
 
 Key job responsibilities
 
 
 <ul>
 <li>
 You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product.
 </li>
 <li>
 You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns.
 </li>
 <li>
 You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders.
 </li>
 <li>
 You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders.
 </li>
 <li>
 You thrive in an agile and fast-paced environment on highly visible projects and initiatives.
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
 </li>
 <li>
 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
 </li>
 <li>
 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
 </li>
 <li>
 Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
 </li>
 <li>
 Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
 </li>
 <li>
 Knowledge of machine learning concepts and their application to reasoning and problem-solving
 </li>
 <li>
 Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
 </li>
 <li>
 Experience applying quantitative analysis to solve business problems and making data-driven business decisions
 </li>
 <li>
 Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
 </li>
 <li>
 Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.
 
 
 </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.
 
 
 The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
 
 
 USA, WA, Seattle - 108,300.00 - 160,000.00 USD annually
 
 
 
 
 Company
 
 - Amazon.com Services LLC
 
 
 Job ID: A3206663
</div>

Data Scientist I, SHAKE

Starbucks

<div>
 
 Now Brewing &ndash; Data Scientist! #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 Data Scientist on the Data and Analytics (D&amp;A) team, you will be responsible for developing, enhancing, and maintaining analytical models and optimization algorithms. Your work will translate complex analyses into actionable business insights, empowering leaders to make data-driven decisions.
 
 
 You will collaborate closely with cross-functional teams&mdash;including Finance, Store Development, Retail Testing, Supply Chain, Marketing, Product, and Customer teams&mdash;to support strategic initiatives and influence key business decisions.
 
 
 
 
 As a data scientist, you will&hellip;
 
 
 
 
 <ul>
 <li>
 Conduct Exploratory Data Analysis - Analyze large-scale datasets through data wrangling, feature engineering, and statistical exploration. Build reusable data pipelines using tools such as Pandas, Databricks SQL, and Spark to uncover trends, prepare raw data for modeling, and generate actionable insights.
 </li>
 <li>
 Develop and Maintain Analytical Models - Design, enhance, and sustain statistical/analytical models tailored to specific domains such as store testing and experimentation, store development, supply chain, and marketing.
 </li>
 <li>
 Build Predictive and Descriptive Models - Leverage historical data, domain attributes, and external signals to develop models that address diverse business challenges and improve decision-making.
 </li>
 <li>
 Collaborate Cross-Functionally - Partner with teams across data engineering, operations, product, supply chain, and more to translate business needs into scalable data science solutions.
 </li>
 <li>
 Influence Strategic Planning - Provide data-driven recommendations to senior leaders, contributing to long-term strategies and business roadmaps.
 </li>
 <li>
 Demonstrate Curiosity and a Growth Mindset - Tackle complex problems with intellectual curiosity, continuously explore new features and methodologies, and stay up-to-date with industry trends and best practices.
 </li>
 <li>
 Thrive in a Collaborative, Impact-Driven Team - Join a high-performing, supportive team that values innovation, continuous learning, and delivering meaningful business outcomes.
 
 
 </li>
 </ul>
 
 We&rsquo;d love to Hear From People With
 
 
 
 <ul>
 <li>
 Bachelors+ with concentration in quantitative discipline &ndash; Stats, Math, Comp Sci, Engineering, or similar discipline. Masters preferred. Minimum of 1 year of experience
 </li>
 <li>
 Proficiency in coding languages for data preparation and modeling, including SQL for querying large datasets and Python for building pipelines and statistical models
 </li>
 <li>
 Solid understanding of statistical concepts, and techniques, such as regression, classification, decision trees, clustering, and causal inference, with practical experience applying them to real-world problems
 </li>
 <li>
 Experience with data visualization tools and techniques (e.g., Tableau, Power BI) to communicate insights effectively to technical and non-technical audiences
 </li>
 <li>
 Demonstrated curiosity and analytical rigor, with a strong ability to explore complex datasets, identify patterns, and generate actionable insights
 </li>
 <li>
 Excellent attention to detail, along with strong written and verbal communication skills to collaborate across cross-functional teams and present findings to stakeholders
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 
 
 <ul>
 <li>
 Familiarity with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments
 
 
 </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.
 
 
 <ul>
 <li>
 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>

data scientist - Data & Data Science (Seattle, WA)

Opendoor

<div>
 
 Data Scientist, Pricing
 
 
 
 
 
 Location: Hyrbrid 4 onsite, 1 remote
 
 Seattle WA.
 
 
 
 Opendoor is transforming one of the largest, most complex markets in the world &mdash; residential real estate &mdash; using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company&rsquo;s financial performance.
 
 
 We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You&rsquo;ll operate at the intersection of economics, machine learning, experimentation, and product strategy &mdash; tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory &mdash; and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.
 
 
 
 What You&rsquo;ll Do
 
 
 
 
 <ul>
 <li>
 Build and maintain pricing metrics, dashboards, and frameworks.
 </li>
 <li>
 Run experiments and causal analyses to measure impact and drive decisions.
 </li>
 <li>
 Develop predictive + statistical models that improve pricing accuracy.
 </li>
 <li>
 Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
 </li>
 <li>
 Deliver insights and narratives that inform executive strategy.
 
 
 
 </li>
 </ul>
 
 Skills &amp; Qualifications
 
 
 
 
 <ul>
 <li>
 Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
 </li>
 <li>
 Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
 </li>
 <li>
 Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
 </li>
 <li>
 Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
 </li>
 <li>
 Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
 </li>
 <li>
 High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
 </li>
 <li>
 Effective communicator &mdash; able to tell the story behind the model to both highly technical and non-technical audiences.
 </li>
 <li>
 8+ years of experience in data science, product analytics, or a similar quantitative role.
 
 
 
 </li>
 </ul>
 
 Base salary range for this role varies. Generally, the base salary range is $186,000 &ndash; $256,000 annually + RSUs + ESPP + additional employee benefits (medical/dental/vision, life insurance, unlimited PTO, 401K).
 
 
 
 #
 
 
 At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We&rsquo;ve built an end-to-end online experience that has already helped thousands of people and we&rsquo;re just getting started.
 
 
</div>

Data Scientist

Serko Ltd

<div>Serko is a cutting-edge tech platform in global business travel &amp; expense technology. When you join Serko, you become part of a team of passionate travellers and technologists bringing people together, using the world&rsquo;s leading business travel marketplace. We are proud to be an equal opportunity employer, and we embrace the richness of diversity, showing up authentically to create a positive impact. There's an exciting road ahead of us, where travel needs real, impactful change.
With offices in New Zealand, Australia, North America, and China, we are thrilled to be expanding our global footprint, landing our new hub in Bengaluru, India. With a rapid growth plan in place, we&rsquo;re hiring people from different backgrounds, experiences, abilities, and perspectives to help us build a world-class team and product. 
 
This role can be based in West Coast USA - we would be open to candidates in other locations as well with proven experience and expertise. 
Requirements 
We are building a foundational AI division at Serko and looking for a Senior Data Scientist to help us move from concept to MVP at velocity. 
This is a hands-on role for someone who prefers building over maintaining. You&rsquo;ll be implementing models within AI-agentic environments, specifically focusing on Recommender Systems, Ranking algorithms, and Reinforcement Learning. 
 
What you'll do<ul><li>
Architect and lead the deployment of sophisticated data science solutions that define the technical direction for Serko&rsquo;s AI-agentic ecosystem.</li><li>
Design the foundational frameworks for model integration within multi-agent environments, overseeing the implementation of high-scale Recommender Systems, Ranking algorithms, and advanced Deep Learning architectures (e.g., Heterogeneous Graph Transformers).</li><li>
Set the standard for technical excellence and velocity, establishing the protocols for scoping and prioritizing complex, cross-functional projects.</li><li>
De-risk the most ambiguous and high-stakes technical challenges, proactively adapting emerging AI technologies to ensure Serko remains a market leader.</li><li>
Partner with Leadership to co-create AI-first product strategies, ensuring the long-term roadmap is anchored in technical feasibility and measurable commercial outcomes.</li><li>
Anticipate market shifts and technological risks, identifying long-term opportunities that leverage proprietary data to create a competitive &quot;moat.&quot;</li><li>
Command executive-level influence by translating complex technical trajectories into strategic business cases for the C-suite and key global partners.</li><li>
Sponsor and elevate the technical community, raising the collective &quot;technical ceiling&quot; of the organization through high-level mentorship and the establishment of best practices.</li></ul>
What you'll bring<ul><li>
At least 8-10+ years of proven experience building and scaling production-grade ML systems that have moved the needle on global business metrics.</li><li>
Deep technical mastery in machine learning and applied statistics, with a track record of implementing &quot;bleeding-edge&quot; techniques in a commercial environment.</li><li>
Authority in experimentation and systems design, with the ability to build for extreme scalability, maintainability, and reliability across global regions.</li><li>
Executive-level communication skills, with a demonstrated ability to influence organizational strategy and navigate complex stakeholder landscapes.</li><li>
Strategic product intuition, understanding how to balance long-term architectural health with the immediate needs of a fast-paced product development cycle.</li><li>
Proven technical leadership, with experience guiding senior engineers/scientists through complex pivots and high-pressure launches.</li><li>
Advanced software engineering fluency (Python and modern data stacks), with a focus on building modular, reusable, and production-hardened AI components.</li><li>
Visionary and resilient mindset, comfortable owning the &quot;blank page&quot; and driving clarity in environments of extreme ambiguity.</li></ul> 

Benefits 
At Serko, we aim to create a place where people can come and do their best work. This means you&rsquo;ll be operating in an environment with great tools and support to enable you to perform at the highest level of your abilities, producing high-quality and delivering innovative and efficient results. Our people are fully engaged, continuously improving, and encouraged to make an impact.
Some of the benefits of working at Serko are:<ul><li>
A competitive base pay</li><li>
Medical Benefits</li><li>
Discretionary incentive plan based on individual and company performance</li><li>
Focus on development: Access to a learning &amp; development platform and opportunity for you to own your career pathways</li><li>
Flexible work policy</li><li>
The pay range is between $184,000 - $270,000 USD as a base salary offering annually.</li></ul></div>

Principal Data Scientist

Data Scientist, Product Analytics

<div>
 We are seeking experienced Data Scientists to join our team and drive impact across various product areas. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
 
 
 Data Scientist, Analytics (Technical Leadership) Responsibilities:
 
 
 <ul>
 <li>
 Work with complex data sets to solve challenging problems using analytical and statistical approaches
 </li>
 <li>
 Apply technical expertise in quantitative analysis, experimentation, and data mining to develop product strategies
 </li>
 <li>
 Identify and measure success through goal setting, forecasting, and monitoring key metrics
 </li>
 <li>
 Partner with cross-functional teams to inform and execute product strategy and investment decisions
 </li>
 <li>
 Build long-term vision and strategy for programs and products
 </li>
 <li>
 Collaborate with executives to define and develop data platforms and instrumentation
 </li>
 <li>
 Effectively communicate insights and recommendations to stakeholders
 </li>
 <li>
 Define success metrics, forecast changes, and set team goals
 </li>
 <li>
 Support developing roadmaps and coordinate analytics efforts across teams
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 </li>
 <li>
 Mathematics, Statistics, Operations Research) 5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab)
 </li>
 <li>
 8+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
 </li>
 <li>
 Experience working effectively with and leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
 </li>
 <li>
 Experience with predictive modeling, machine learning, and experimentation/causal inference methods
 </li>
 <li>
 Experience communicating complex technical topics in a clear, precise, and actionable manner
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy
 </li>
 <li>
 Masters or Ph.D. Degree in a quantitative field
 </li>
 <li>
 Bachelor's Degree in an analytical or scientific field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research)
 </li>
 <li>
 10+ years of experience doing complex quantitative analysis in product analytics
 </li>
 <li>
 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 </li>
 <li>
 Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 </li>
 <li>
 Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 
 
 </li>
 </ul>
 About Meta:
 
 
 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
 
 
 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
 
 
 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
 
 
 $210,000/year to $281,000/year + bonus + equity + benefits
 
 
 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
</div>

Data Scientist, Analytics (Technical Leadership)

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
AWS is one of Amazon&rsquo;s largest and fastest growing businesses, serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises use information technology. We are looking for entrepreneurial, analytical, creative, flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced, innovative team that is making history, this is the place for you. 
 
AWS Central Economics &amp; Science (ACES) drives best practices for objectively applying economics and science in decision making across AWS. The team collaborates with AWS science and business teams to identify, frame, and analyze complex and ambiguous problems of the highest priority. Through data-driven insights and modeling, ACES supports strategic decision-making across the AWS global organization, including sales operations and business performance optimization.
 
 
The ACES Sales Channels team is hiring an Applied Scientist (Senior or below) to advance our mission of providing rigorous, causal-inference-driven recommendations for AWS sales optimization. This role will focus on building ML systems with a causal modeling foundation, designing seller incentive mechanisms, and developing intervention strategies across the entire sales motion. 
 
Key job responsibilities 
<ul><li>Causal ML System Development: Build and deploy machine learning models that emphasize causal inference, ensuring recommendations are grounded in valid interventions</li><li>Incentive Design: Define and model incentives that drive desirable behaviors across AWS sales channels, partner programs, and reseller ecosystems</li><li>Stakeholder Collaboration: Work with business stakeholders to understand requirements, validate approaches, and ensure practical applicability of scientific solutions</li><li>Scientific Rigor: Promote findings at internal conferences and contribute to the team's reputation for methodological excellence</li></ul> 
A day in the life 
The ACES Sales Channels team works on understanding and optimizing AWS's sales channels, both direct (generalist and specialist sellers) and indirect (partners and Marketplace). Our work falls into three core areas: developing rigorous causal measurement and modeling frameworks using cutting-edge economics and statistical methods; designing programs and incentives to improve customer and business outcomes; and building ML-based recommendation systems for sellers, partners, and other AWS stakeholders. 
 
About the team 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Hybrid Work 
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.</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</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. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
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. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 192,200.00 - 260,000.00 USD annually 
USA, NY, New York - 183,800.00 - 248,700.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Senior Applied Scientist, AWS Central Economics and Science

Explore 155+ Senior data scientist in Seattle this April. Find roles across top companies and apply now to boost your career.