data scientist ii

WorkGenius Group

<div>
 
 Title:
 
 Data Scientist II
 
 
 
 Industry:
 
 Tech
 
 
 
 Location:
 
 Culver City, CA
 
 
 
 Duration:
 
 12 months
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Build and maintain machine learning models, forecasting tools, and optimization frameworks
 </li>
 <li>
 Analyze marketing performance and identify trends to improve campaign effectiveness
 </li>
 <li>
 Conduct causal analysis to evaluate the impact of marketing initiatives
 </li>
 <li>
 Develop models to measure upper-funnel marketing performance across diverse data sources
 </li>
 <li>
 Collaborate with cross-functional teams to solve business problems using data
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree with 3+ years of experience, or Master&rsquo;s degree with 2+ years in data science or related field
 </li>
 <li>
 Strong foundation in statistics, probability, and machine learning techniques
 </li>
 <li>
 Proficiency in SQL and Python or R for data analysis
 </li>
 <li>
 Experience with supervised and unsupervised learning methods
 </li>
 <li>
 Understanding of digital marketing data and KPIs (e.g., social, SEO, paid media)
 
 
 </li>
 </ul>
 
 Skills
 
 
 
 <ul>
 <li>
 Data Science
 </li>
 <li>
 Machine Learning
 </li>
 <li>
 Causal Analysis
 </li>
 <li>
 Marketing Performance
 </li>
 <li>
 Statistical Analysis
 </li>
 <li>
 SQL
 </li>
 <li>
 Python
 </li>
 <li>
 Data Visualization
 </li>
 <li>
 Digital Marketing
 </li>
 <li>
 Analytical Skills
 
 
 </li>
 </ul>
 Hourly rate is commensurate with experience and is an estimated range provided by WorkGenius.
 
 
 ref_id: 34755934-4182-4f5b-a324-b304ab950680
 
 
</div>

Data Scientist II

Careem

<div>
 
 About the Company
 
 
 
 Careem is building the Everything App for the greater Middle East &mdash; making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people&rsquo;s lives and build an awesome organisation that inspires.
 
 
 Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region&rsquo;s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.
 
 
 
 
 We&rsquo;re now entering our next chapter &mdash; one powered by AI. We&rsquo;re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it&rsquo;s streamlining operations, enhancing customer experience, or reimagining internal systems &mdash; we want people who can make Careem work smarter and move faster.
 
 
 
 
 
 
 About the Role
 
 
 
 
 We&rsquo;re looking for senior technical leaders who can architect and scale intelligent systems that architect the "brain" of our dark store operations. As a senior data scientist you won&rsquo;t just be building models, you&rsquo;ll be optimizing the lifecycle of millions of items from the moment they leave a supplier to the moment they reach a customer&rsquo;s doorstep in under 20 minutes. You will tackle the classic "perishable trade-off" ensuring our shelves are always stocked with what customers want, while ruthlessly minimizing wastage and maximizing every square centimetre of our dark store floor space.
 
 
 
 
 What You'll Do
 
 
 
 
 <ul>
 <li>
 Demand Forecasting: Build and deploy high-precision forecasting models to predict hyper-local demand at the SKU-store level.
 </li>
 <li>
 Inventory &amp; Availability: Develop replenishment algorithms that balance In-Stock Availability with the risk of expiry, specifically for high-turnover perishables.
 </li>
 <li>
 Wastage Mitigation: Use ML to identify items at risk of expiring and trigger automated interventions including reduced-to-clear discounting, intra-store replenishment etc.
 </li>
 <li>
 Dynamic Pricing &amp; Discounts: Design and A/B test pricing strategies that move inventory efficiently without eroding margins.
 </li>
 <li>
 Space Management: Optimize dark store space determining which items should be stored where within the dark store to minimize picker travel time and maximize storage density.
 </li>
 <li>
 End-to-End Ownership: Work closely with Product Managers and Supply Chain Operations to turn your models into production-level code that dictates real-world logistics.
 
 
 </li>
 </ul>
 
 
 What You'll Need
 
 
 
 
 <ul>
 <li>
 Academic Background &amp; Experience: 8+ years of experience in Data Science, ideally in E-commerce, Q-commerce, or Supply Chain. A background in Operations Research or Statistics. Hands-on proficiency in Python, Spark and ML frameworks. Experience with real-time inference systems and model monitoring in production. Strong understanding of experimentation, A/B testing, and causal inference. Demonstrated ability to drive architectural decisions across teams.
 </li>
 <li>
 Technical Skills: Professional-grade Python and SQL. Experience with optimization libraries (like Gurobi, CPLEX, or PuLP) and ML frameworks (XGBoost, LightGBM, or PyTorch).
 </li>
 <li>
 Problem Solving: Experience with Stochastic Optimization or Reinforcement Learning for inventory management is highly preferred.
 </li>
 <li>
 Business Intuition: You understand that a 1% reduction in wastage across 100+ stores translates to millions in saved EBITDA.
 </li>
 <li>
 Communication Skills: Excellent communication skills and ability to translate complex modelling trade-offs into business impact.
 
 
 </li>
 </ul>
 
 
 What We&rsquo;ll Provide You
 
 
 
 
 
 
 We Offer Colleagues The Opportunity To Drive Impact In The Region While They Learn And Grow. As a Full Time Careem Colleague, You Will Be Able To
 
 
 <ul>
 <li>
 Work and learn from great minds by joining a community of inspiring colleagues.
 </li>
 <li>
 Put your passion to work in a purposeful organisation dedicated to creating impact in a region with a lot of untapped potential.
 </li>
 <li>
 Explore new opportunities to learn and grow every day.
 </li>
 <li>
 Work 4 days a week in office &amp; 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year. (If you are in an individual contributor role in tech, you will have 2 office days a week and 3 to work from home.)
 </li>
 <li>
 Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.
 </li>
 </ul>
</div>

Senior Data Scientist II - Supply Chain

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. 
 
We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores. 
 
We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action. 
 
Key job responsibilities 
 
Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models 
Working with technical and non-technical stakeholders across every step of science project life cycle 
Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models 
Innovating by adapting new modeling techniques and procedures 
Presenting research results to our internal research community<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ 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>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>Experience applying theoretical models in an applied environment</li><li>Bachelor's degree</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience effectively communicating complex concepts through written and verbal communication</li><li>Master's degree</li><li>Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems</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. 
 
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, Sunnyvale - 157,300.00 - 212,800.00 USD annually 
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist II, Amazon Stores Finance Science

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
We are seeking an experienced Data Scientist to drive scientific tooling supporting how Amazon's business customers interact with LTPF forecasts and plans. As a science leader within the LTPF, you will be responsible for building to the multi-year roadmap for customer engagement, ensuring that business stakeholders across Amazon can seamlessly access, understand, and act upon our forecasting outputs. In this role, you will manage the lifecycle of complex, cross-functional programs that transform how Operations, Stores, and Finance teams leverage LTPF insights for strategic decision-making. You will work with scientists, economists, engineers, and business customers to architect the customer interaction experience, including viewing capabilities, auditing tools, what-if analysis frameworks, and forecast intervention workflows. 
 
This role might be for you if you have interest and experience in: 
<ul><li>Leading large, cross-functional planning and strategy workstreams that impact Amazon's topline growth</li><li>Defining multi-year program vision and strategy while balancing short-term execution</li><li>Regularly presenting to VP and SVP level leaders</li><li>Prioritizing operational excellence work alongside feature delivery on a roadmap</li><li>Showing strong business acumen with strategic, analytical, and critical thinking</li><li>Managing planning calendars and strategic review mechanisms</li><li>Driving organizational alignment across multiple teams and stakeholders</li></ul> 
Key job responsibilities 
As a Data Scientist in LTPF (Long-Term Planning &amp; Forecasting): 
<ul><li>You will develop causal inference models, automated explainability frameworks, and variance bridging methodologies that translate LTPF's forecasts and plans into actionable business intelligence.
</li><li>Your work will enable leadership to understand why forecasts and actuals diverge, what is driving demand shifts, and how strategic decisions propagate through the planning ecosystem.</li><li>You will build automated Plan-vs-Actual and Actual-vs-Actual variance decomposition models that quantify the contribution of individual demand drivers to observed gaps across revenue, price, units, inventory, and capacity metrics at multiple granularities to serve audiences from working-level analysts to VP-level planning reviews cycles.</li><li>You will build and maintain a causal model library with standardized hypothesis generation and validation pipelines, applying techniques from causal inference, time-series econometrics, and Bayesian methods. Each model will include calibrated confidence scoring and reusable components that scale across worldwide marketplaces.</li><li>You will develop GenAI-powered narrative generation capabilities that synthesize quantitative variance outputs into human-readable performance summaries and design automated hypothesis ranking to determine which demand drivers are most responsible for observed forecast error.</li></ul> 
A day in the life 
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
 
 
The benefits that generally apply to regular, full-time employees include:
 
<ul><li>Medical, Dental, and Vision Coverage
</li><li>Maternity and Parental Leave Options
</li><li>Paid Time Off (PTO)
</li><li>401(k) Plan
</li></ul> 
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
 
 
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you&rsquo;re passionate about this role and want to make an impact on a global scale, please apply! 
 
About the team 
The Long-Term Planning and Forecasting (LTPF) organization is dedicated to answering some of Amazon's most important strategic questions: Where will Amazon's growth come from in the next year? What about over the next five years? Which product lines are poised to grow significantly? Are we investing appropriately in our infrastructure? How do our customers react to changes in prices, product selection, or delivery times? Are our infrastructure investments optimal for the level of demand we expect?</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ 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>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of guiding and coaching a group of researchers experience</li><li>1+ years of working with or evaluating AI systems 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><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in Python, Perl, or another scripting language</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience effectively communicating complex concepts through written and verbal communication</li><li>Experience in forecasting analyses</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, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist II, Long Term Planning and Forecasting

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. 
 
The Data, Insights, Science and Optimization, Consumer Product and Tech (DISCO CPT) team is looking for a Data Scientist to join a team of Data Scientists, Analytics Leads, Business Intelligence Engineers and Data Engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power product for personalized experiences. The team focuses on accelerating Amazon Music customer growth by empowering Product teams to make sound, customer-centric decisions through data and insights. We build data pipelines, science models, self-service analytics, insights and dashboards, deliver engagement and retention at scale. In this role, you will pioneer and execute advanced analytics and experimentation efforts for the Amazon Music product team. You will work with stakeholders and partners to deliver experimentation insights, author scientific artifacts, build scalable models to advance our analytics and science products. The ideal candidate must be willing to effectively lead science solutions, prioritize across multiple stakeholders and projects and be ready to jump into a fast-paced, dynamic and fun environment. 
 
Key job responsibilities 
<ul><li>Data Scientist II on this role will be a thought partner to Product and Engineering organizations through their expertise in experimentation, statistical modeling and advanced analytics</li><li>Conceptualize and drive strategic growth areas: retention, voice + visual engagement, experimentation, Gen AI initiatives, and product excellence.</li><li>Bridge science, analytics, and engineering to deliver solutions informing strategic decisions on AM technology investments and long-term business performance</li><li>Drive experimentation, measurement efficiency tooling, and ROI tracking for AM leadership</li><li>Build and maintain causal models to understand customer sentiment and its impact on key engagement/retention metrics</li><li>Develop structural and predictive models using data science workflows to deliver measurable customer results</li></ul> 
A day in the life 
<ul><li>Lead strategic initiatives across visual and voice experiences, experimentation and customer retention stakeholders</li><li>Conduct experimentation, build causal models to better understand key drivers for customer retention
</li><li>Evaluate existing metrics and lead deep dives to ensure the right measurement framework is leveraged to measure and enhance user adoption through visual and voice interfaces</li><li>Partner with product managers to translate business questions into actionable science projects</li><li>Influence product roadmaps through data-driven insights on customer behavior patterns</li><li>Identify and resolve customer experience friction points with cross-functional teams</li><li>Drive adoption of best practices and innovative solutions across the organization</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Bachelor's degree</li><li>2+ years of data scientist experience</li><li>3+ 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>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in Python, Perl, or another scripting language</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</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 - 157,300.00 - 212,800.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, Amazon Music - DISCO

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. 
 
We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. 
As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
Key job responsibilities 
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. 
Specific responsibilities include: 
<ul><li>Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features</li><li>Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings</li><li>Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases</li><li>Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance</li><li>Develop and refine annotation guidelines and quality frameworks for evaluation tasks</li><li>Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies</li><li>Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements</li><li>Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts</li><li>Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets</li></ul> 
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>2+ years of data scientist experience</li><li>3+ 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>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of working with or evaluating AI systems 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><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</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. 
 
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, Santa Clara - 157,300.00 - 212,800.00 USD annually 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, AWS Quick Data

Amazon Web Services (AWS)

<div>
 
 Description
 
 
 
 Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale.
 
 
 We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale.
 
 
 As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
 Key job responsibilities
 
 
 In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.
 
 
 
 Specific Responsibilities Include
 
 
 
 <ul>
 <li>
 Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
 </li>
 <li>
 Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings
 </li>
 <li>
 Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
 </li>
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 Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
 </li>
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 Develop and refine annotation guidelines and quality frameworks for evaluation tasks
 </li>
 <li>
 Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
 </li>
 <li>
 Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
 </li>
 <li>
 Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
 </li>
 <li>
 Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets
 
 
 </li>
 </ul>
 
 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.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 2+ years of data scientist experience
 </li>
 <li>
 3+ 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>
 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
 </li>
 <li>
 1+ years of working with or evaluating AI systems 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>
 <li>
 Experience applying theoretical models in an applied environment
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
 </li>
 <li>
 Knowledge of machine learning concepts and their application to reasoning and problem-solving
 </li>
 <li>
 Experience in a ML or data scientist role with a large technology company
 </li>
 <li>
 Experience in defining and creating benchmarks for assessing GenAI model performance
 </li>
 <li>
 Experience working on multi-team, cross-disciplinary projects
 </li>
 <li>
 Experience applying quantitative analysis to solve business problems and making data-driven business decisions
 </li>
 <li>
 Experience effectively communicating complex concepts through written and verbal communication
 
 
 </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.
 
 
 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, Santa Clara - 157,300.00 - 212,800.00 USD annually
 
 
 USA, NY, New York - 153,400.00 - 207,500.00 USD annually
 
 
 USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually
 
 
 
 
 Company
 
 - Amazon Development Center U.S., Inc.
 
 
 Job ID: A10411927
</div>

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