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Staff Data Privacy Engineer Jobs

3,415 active opportunities · Updated for October 2026

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Explore current staff data privacy engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Pinterest
📍 United States• Full-time• Remote• From $164.7K/yr
1mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . What you’ll do: Develop measurement frameworks and metrics to drive data-driven decision making, optimizing for the full user journey. Product recommendations. Clearly communicate recommendations to product and engineering leadership on how we can evolve our Notifications strategy to address shortcomings observed through deep analysis. Opportunity sizing and analysis. Write clear, actionable analyses that help teams identify areas of improvement to our growth strategies. Thought partner to product, engineering, and ML leadership on the Notifications team to prioritize/scope projects and inform the development of the notifications user experience and corresponding ML systems. Improve machine learning models which power notifications delivery and content, via direct contributions, new features/signals, and/or compelling analy

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Pinterest
📍 San Francisco• Full-time• Remote• From $164.7K/yr
1mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We are looking for a Staff Data Scientist for our Ads Delivery. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and uplevel our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world. What you’ll do: Develop a deep, nuanced understanding of the Pinter

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R
1mo ago

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Credit Card business team's mission is to shape Robinhood’s vision in the credit and banking space by delivering smart, customer-focused financial solutions. Our team is dedicated to reshaping the credit landscape and redefining the way people interact with financial services daily. We leverage cutting-edge analytical tools and diverse datasets to build deep understandings of consumer credit behaviors. We aim to make financial services accessible to everyone, building programs that support Robinhood’s broader goals! As a Staff Data Scientist, you will build credit risk models that allow us to better serve our customers and make responsible lending decisions. Credit models are at the heart of all lending decisions. These models will drive decisions ranging from approve/decline, line assignment at origination and future credit limit increases. You will leverage traditional and non-traditional data sources to build highly predictive risk models. You will own the full lifecycle of model development from data prep, model building to model deployment. This role is based in our Menlo Park, CA, or Washington, DC office(s), with in-person attendance expected at least 3 days per w

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Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Talent Management & Analytics team is scaling to its next major milestone—integrating advanced predictive insights and tactical AI into our workforce systems. Our mission is to build the data solutions that help the entire company recruit exceptional talent, design high-performing team structures, and put active organizational insights directly into the hands of everyone making team decisions. Operating at the intersection of data science, product development, and organizational psychology, we are transforming how Robinhood uses data to empower our workforce and anticipate organizational needs. As a Staff Data Scientist, you will serve as the team's technical and strategic anchor, owning the vision, design, and delivery of the high-impact data products that our executives, people partners, and line managers rely on every day. Your focus will be entirely on solving meaningful organizational problems: understanding what enables exceptional talent to thrive, accelerating team performance, and designing proactive strategies that support long-term retention across Robinhood. This is a unique opportunity to apply state-of-the-art language models and predictive analytics to

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S
1mo ago

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team You’ll be joining the data science team at Stripe responsible for our overall infrastructure, with a special focus on Stripe’s security. Projects include, but are not limited to: Leverage internal telemetry and logs to understand and design secure and safe access controls to sensitive data; Develop methods to model, quantify, and ultimately de-risk security-related incidents on Stripe data, assets, and networks; Collaborate across the company with engineering, PMs, and others to better understand, measure, and ultimately detect various malicious attack vectors. You will act as a key strategic data partner to the Security organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe keeps and maintains the highest level of safety and security for critical business assets and customer data. What you'll do Responsibilities Provide senior technical direction to data teams on horizontal technical areas, including detection, modeling, metrics, observability, etc. Assume hands-on leadership, especially when helping teams resolve complex problems through iterative execution. Identify broad company problems and opportunities that can be tackled through data science Work with relevant teams to design and build the quantitative outputs and artifacts that deliver outsized value to our users and our business. Provide data-driven guidance to cross-functional partners on strategy for tracking and p

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Stripe
📍 United States• Full-time
1mo ago

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Risk Data Science team builds the data foundations, models, and measurement frameworks that power Stripe's risk and product decisions — from underwriting and reserves to merchant interventions and enablements. We're at an inflection point: as Stripe increasingly offers risk capabilities as a product to platforms and users, we need a data leader to shape how we build, measure, and evolve our risk data strategy across the What you’ll do We are looking for an experienced data analyst to drive the data strategy for our risk as a product offering. Define the metrics, data products, and analytical frameworks needed as Stripe brings risk capabilities to platforms and connected accounts at scale. Partner with Product, Engineering, and Risk leadership to ensure data investments align with the product roadmap. You will design metrics, pipelines, and data products that serve as the analytical backbone for risk decisioning. You will own the definition, reliability, and visibility of our most important risk metrics. Establish a canonical set of north star and operational metrics and ensure they are trustworthy, well-documented, and consistently surfaced to the right audiences. Build and maintain the infrastructure that keeps these metrics accurate as our data and product landscape evolves, including clear ownership, alerting on regressions, and scalable pipelines that reduce the cost of keeping insights current. You will also own and evolve Str

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Taskrabbit
📍 San Francisco• Full-time• $170K – $225K/yr
1mo ago

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: W e are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA). About the Role Data Science plays a crucial role in driving impact at Taskrabbit. As a member of the team, you will help drive our business strategy forward through predictive insights. We are seeking a highly skilled and motivated Staff Data Scientist to join us, working closely with cross-functional teams from product, finance, engineering, risk and operations to provide data-driven insights and solutions that enhance our products and accelerate growth while minimizing marketplace losses.

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Snowflake
📍 Menlo Park• Full-time
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Staff Data Scientist, Finance About the Team The Finance Data Science team builds the forecasting and decision systems that power Snowflake's financial planning, operating cadence, and long-term strategy. Our work informs executive decision-making, product and go-to-market priorities, resource allocation, pricing, and cross-functional decisions across Finance, Product, Sales, and Data Science. We are expanding a driver-based revenue modeling platform that translates product and workload activity into trusted financial outcomes. The program began with one product category and will scale a common modeling and publishing framework across Snowflake's product categories. The models are highly visible, refreshed frequently, and designed for self-service scenario planning and business reviews. The Role We are hiring a Staff Data Scientist to lead the next phase of Snowflake's driver-based revenue modeling program. This role is not just about building models. It is about creating reliable, explainable, production-grade decision systems that connect upstream business and product levers to revenue outcomes. You will own high-impact, open-ended problems spanning driver identification, revenue decomposition, leading indicators, cohort and use-case modeling, scenario analysis, and multi

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R
17 days ago

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most comp

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Coinbase
📍 - USA• Full-time• Remote• From $207.5K/yr
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Staff Data Scientist on the Data Science team within the Platform group, you'll own pricing experimentation and strategy for Coinbase's Consumer & Business products. This team partners directly with Product, Engineering, and Design to turn deep analytical expertise into decisions that move the company's bottom line. You'll design and analyze pricing tests, build models that identify optimal strategies, and communicate findings to executives and cross-functional leaders. What you'll do: Own end-to-end pricing experimentation, from test design through analysis and recommendation Build and refine pricing models and evaluation frameworks that determine optimal pricing strategy across consumer products Partner with Product, Engineering, and Finance stakeholders to develop pricing vision, roadmap, and priorities Develop and maintain data pipelines and data models that power pricing analytics with production-grade craftsmanship Synthesize complex findings into clear, actionable recommendations and present them to senior leadership Required Skills and Experience: 8+ years of experience in data science with a focus on pricing experimentation, causal inference, and statistical modeling (PhD preferred, or Master's in Economics, Statistics, or related quantitative field) 5+ years directly leading pricing or experimentation workstreams, including designing A/B tests and

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Biohub
📍 Ny Hybrid• Full-time• Hybrid• From $241K/yr
1mo ago

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Biohub is a 501(c)(3) biomedical research organization building the first large-scale scientific initiative combining frontier AI with frontier biology to solve disease. We build the technology to help scientists around the world use AI-powered biology to study how cells operate, organize, and work as part of systems to understand why disease happens and how to correct it. With our compute capacity, AI research and engineering, and state-of-the-art technology for measuring, imaging, and programming biology, we are enabling scientists worldwide to use AI-powered biology to advance our understanding of human health. The Opportunity The role is part of the Data Engineering team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems. The data that trains biological frontier models comes in dozens of modalities (sequences, images, spatial coordinates, time series, molecular structures, metadata, publication artifacts) each with its own noise characteristics, biases, and information content. The question of how to represent this data for learning is one of the most important open problems in biological AI. As a Senior Staff Data Engineer at Biohub, you'll be designing systems that ingest data from public repositories, transform heterogeneous biological formats into AI-rea

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Snowflake
📍 Menlo Park• Full-time
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Data Analytics and AI org (DAA) is actively seeking a Staff Data Scientist, GTM to provide technical leadership for Snowflake’s next generation of AI & Machine Learning powered GTM decision systems. You will contribute to high-impact work across sales and marketing: propensity models across the GTM funnel, measuring the causal effect of GTM investments and interventions, and recommending actions for accounts, leads, opportunities, and customers. This role goes beyond developing models. You will define how decision systems are designed, evaluated, productionized, and integrated into the workflows of sellers, marketers, and business leaders. You will establish reusable technical standards, guide investment across use cases, and ensure that sophisticated methods translate into measurable business impact. What You’ll Do • Set the technical direction for a portfolio of AI & Machine Learning GTM decision systems spanning Sales and Marketing. • Develop pipeline forecasting methods that model stage progression, conversion, deal timing • Build account, lead, opportunity, and customer models that identify propensity, risk, potential, and likely next outcomes. • Develop recommendation and next-best-action systems that determine where GTM teams should focus, which action to

pythonsqlmachine learning
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Tubi - Canada
📍 Toronto• Full-time• From C$1.4M/yr
17 days ago

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

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