Plaid

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.<h2>Senior Data Scientist - Network Value (Plaid App)</h2>The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go.You’ll be a Senior Data Scientist supporting Plaid App, a critical user-facing product within Plaid’s Network Value portfolio. In this role, you’ll become a data and analytical thought partner to product managers and engineers, helping drive data-informed product development as the team launches and scales the product from 0 to 1. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and metrics tied to business goals, and support feature ship decisions through experimentation. You’ll also help identify new ways Plaid App can move top-line outcomes and influence prioritization, roadmapping, and execution across cross-functional partners. <h2>Responsibilities</h2><ul><li>Champion a data-first approach to decision-making across the organization as Plaid App is built and scaled, serving as the data and analytical thought partner to product managers, engineers, and cross-functional stakeholders.</li><li>Translate ambiguous business and product questions into clear analytics projects and decision frameworks, and perform ad-hoc and strategic analyses to identify opportunities to improve user outcomes and business performance.</li><li>Build and maintain data models, dashboards, core metrics, OKRs, and success metrics that improve visibility into Guard performance and quantify progress against business goals.</li><li>Design and analyze experiments to support feature launch and iteration decisions, and partner on Airflow- and dbt-powered data pipelines that enable trustworthy analytics and scalable reporting.</li><li>Identify novel ways to impact top-line OKRs and influence stakeholders on prioritization, roadmapping, and execution, while exploring ML prototypes and causal inference approaches where they can improve product or decision quality.</li></ul><h2> Qualifications</h2><ul><li>5-8+ years of experience as a Data Scientist or in a related analytics or data-focused role</li><li>Fintech experience, including experience working with raw fintech data</li><li>Experience launching direct-to-consumer products from 0 to 1</li><li>Experience with experimentation, ad-hoc analysis, and developing strategic insights</li><li>Strong SQL skills and experience creating metrics that drive alignment with stakeholders</li><li>Experience building or partnering closely on data pipelines using Airflow and dbt</li><li>Strong communication skills and experience partnering cross-functionally with product managers, engineers, and other stakeholders</li><li>Experience driving data-driven performance for user-facing products</li><li>Track record of identifying novel ways to impact a top-line OKR and influencing stakeholders on prioritization, roadmapping, and/or execution</li></ul><h2>Nice to have</h2><ul><li>Experience with causal inference</li><li>Experience with machine learning</li><li>Python proficiency</li></ul>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.Please review our Candidate Privacy Notice <a target="_blank" rel="noopener noreferrer ugc" href="https://plaid.com/legal/#candidate-privacy-notice">here</a>. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Senior Data Scientist - Network Value (Guard)

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.We are the Data Foundation &amp; AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management, and observability. In this role, you will establish rigorous evaluation frameworks to measure model performance across diverse use cases and build scalable, repeatable pipelines that translate research into production impact. You will also partner closely with teams across the organization to define how products integrate with and adapt foundation models, enabling reusable ML infrastructure and reducing duplicated modeling efforts. As a senior technical leader, you will mentor engineers across experience levels, elevate engineering and experimentation standards, and communicate technical advancements both internally and externally as a representative of Plaid’s AI and machine learning capabilities. Responsibilities:<ul><li>Owning the end-to-end technical strategy for a foundation model built on one of the world's richest financial datasets, from pretraining architecture to production serving.</li><li>Doing research that ships: driving decisions from experimentation through production systems that serve real customers and power multiple product teams.</li><li>Working across the full ML stack, including pretraining objectives, architecture design, distributed training, serving infrastructure, monitoring, and cross-team integration.</li><li>Setting technical direction and mentoring a high-caliber team, with your work amplifying the capabilities of engineers and product teams across Plaid.</li><li>Helping hundreds of millions of consumers achieve greater financial freedom through the ML capabilities you build and ship.</li></ul>Qualifications:<ul><li>MS: 7–12+ years of industry experience with a demonstrated track record of technical leadership and production delivery.</li><li>PhD: 5–9+ years of industry experience with evidence of technical leadership (tech lead, principal/staff-equivalent roles) and end-to-end production ownership.</li><li>Prior technical leadership experience (tech lead, principal, or staff) with demonstrated cross-team influence and mentorship.</li><li>Deep expertise in Transformers/LLMs/Foundation Models, including large-scale training or domain adaptation.</li><li>End-to-end production ownership; proven track record shipping models through training, serving, monitoring, and iteration in live environments.</li><li>Distributed training experience and strong Python + software engineering fundamentals at a staff level.</li><li>Ability to drive technical alignment across teams: setting standards, defining integration patterns, and influencing beyond your immediate scope.</li><li>Fintech / financial data domain experience - Nice to have</li><li>External publications or open-source contributions - Nice to have</li><li>Experience defining ML platform capabilities (serving infra, feature stores) used across multiple teams. - Nice to have</li></ul>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.Please review our Candidate Privacy Notice <a target="_blank" rel="noopener noreferrer ugc" href="https://plaid.com/legal/#candidate-privacy-notice">here</a>. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Staff Machine Learning Engineer (Research Scientist) - DFAI

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Data Scientist supporting Remember Me. In this role, you’ll become a data and analytical thought partner to product managers and engineers, helping drive data-informed product development for a critical user-facing product. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs quantifying progress against business goals, support feature ship decisions through experimentation, and build ML prototypes and causal inference models. Your work will directly support Conversion and Remember Me Enrolled Profile OKRs and help Plaid grow the size and depth of its Consumer Network.<h2>Responsibilities</h2><ul><li>Champion a data-first approach toward decision-making across the entire organization</li><li>Become the data and analytical thought partner to product managers and engineers</li><li>Translate business questions into analytics projects</li><li>Perform ad-hoc and strategic analyses to identify opportunities for improved outcomes and support business decisions</li><li>Build data models and dashboards to improve visibility into core systems</li><li>Create OKRs quantifying progress against business goals</li><li>Design and analyze experiments to support feature ship decisions</li><li>Build ML prototypes and causal inference models</li></ul><h2>Qualifications</h2><ul><li>5-8+ years of experience as a Data Scientist or in a related analytics or data-focused role</li><li>Experience with experimentation, ad-hoc analysis, and developing strategic insights</li><li>Strong SQL skills and experience creating metrics that drive alignment with stakeholders</li><li>Experience building data pipelines with Airflow and dbt</li><li>Strong communication skills and experience partnering cross-functionally with product managers, engineers, and other stakeholders</li><li>Experience driving data-driven performance for user-facing products</li><li>Track record of identifying novel ways to impact a top-line OKR and influencing stakeholders on prioritization, roadmapping, and/or executionNice to have:<ul><li>Fintech experience and experience working with raw fintech data</li><li>Experience with causal inference, machine learning, and Python</li></ul></li></ul><div> </div>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.Please review our Candidate Privacy Notice <a target="_blank" rel="noopener noreferrer ugc" href="https://plaid.com/legal/#candidate-privacy-notice">here</a>. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Senior Data Scientist - Network Value

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.The Analytics Engineering team owns the full-stack analytics foundation for Plaid's GTM, CGX, NEA and Marketing organizations. We build and maintain the core semantic layer data models (dbt on Databricks), activation layer, and BI surfaces that these teams rely on — and we partner with stakeholders to turn those models into decisions, forecasts, analytics and experiments.As a Senior Analytics Engineer, you’ll also act as an applied data science partner. In addition to core analytics engineering, you’ll work on predictive modeling, experimentation, lifetime value (LTV), and attribution alongside the broader team.As a Senior Analytics Engineer on the Marketing pod, you will be the technical owner of Plaid's Marketing data stack. You will build the dbt models, predictive frameworks, and self-serve data products that Marketing leadership uses to plan spend, measure performance, and drive growth.You'll partner directly with PMM, Growth Marketing, and Marketing leadership to deliver core data models, frameworks, and tools — including LTV, lead scoring, and experimentation tooling — with a north star that aims for prescriptive and production-grade analytics. You'll also help build the AI-powered experiences that let Marketing partners self-serve from our metric layerResponsibilities<ul><li>Own the dbt models and data marts that power Marketing analytics, activation, and reporting. </li><li>Build, validate, and productionize predictive models (lead scoring, LTV, channel attribution, propensity) in partnership with Marketing and GTM stakeholders</li><li>Partner with Marketing leadership on measurement frameworks, experiment design, and spend optimization — translating business questions into analytical answers</li><li>Enable self-serve analytics through AI tools and well-documented semantic models</li><li>Collaborate with ML, Data Engineering, and Ops teams to deliver best-in-class data infrastructure to Marketing</li></ul>Qualifications<ul><li>Bachelor's degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience)</li><li>5+ years of proven experience in analytics engineering, data science, or a closely adjacent function</li><li>Advanced SQL and production-grade data modeling experience — dbt strongly preferred</li><li>Python proficiency for modeling and analysis work</li><li>Hands-on experience with a modern cloud warehouse (Databricks, Snowflake, BigQuery, or Redshift)</li><li>Demonstrated experience shipping predictive models or applied ML in a business context</li><li>Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company</li><li>Strong stakeholder communication and the ability to autonomously drive projects end-to-end</li></ul>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.Please review our Candidate Privacy Notice <a target="_blank" rel="noopener noreferrer ugc" href="https://plaid.com/legal/#candidate-privacy-notice">here</a>. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Senior Analytics Engineer

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.Our Fraud team's mission is to help companies detect and prevent fraud using Plaid's financial network data. We believe that transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention. Our products — including Protect and Signal — operate at network scale and depend on real-world investigation and research to stay ahead of adaptive adversaries.<div> </div>As a Senior Fraud Researcher, you will sit at the intersection of live fraud investigation, applied data science, and product innovation. You will lead complex investigations, translate findings into detection improvements, and collaborate tightly with Data Science, ML, and Product teams to shape the next generation of Plaid's fraud capabilities. This is not a purely operational role — your research directly drives features, model inputs, and product design.Responsibilities:Live Fraud Investigation &amp; Reconstruction<ul><li>Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces</li><li>Provide support to day-to-day fraud operations including SEVs and alert triage</li><li>Reconstruct attacker sequences and hypothesize actor intent and tooling</li><li>Distill patterns from noisy signals into clear narratives and actionable insights</li><li>Bridge investigation outcomes to product and model improvements</li></ul>Signal &amp; Tool Utilization at Scale<ul><li>Operate across Plaid's fraud tooling — dashboards, alerting systems, network signals, and analytics platforms — to detect and validate anomalies</li><li>Stress-test existing capabilities, identify systemic gaps, and define new detection primitives</li><li>Proactively identify gaps in internal fraud tooling and automation, driving enhancements to improve efficiency and scale</li></ul>Product &amp; Model Partnership<ul><li>Collaborate with Data Science, ML/AI, and Product teams to improve labeling, feature sets, evaluation frameworks, and model decay monitoring</li><li>Surface data quality limitations and systematically formalize missing features</li><li>Translate exploratory research into reusable feature pipelines, model inputs, or rule augmentations</li><li>Participate in product discovery, roadmap planning, and post-launch evaluation to ensure fraud-awareness by design</li></ul>Deep Applied Fraud Research<ul><li>Conduct longitudinal and structural analysis of how fraud types manifest in Plaid network data — entity linkages, temporal patterns, attack rotations, tool chains</li><li>Experiment with network/graph analysis, sequence mining, anomaly detection, and custom heuristics where off-the-shelf approaches fail</li></ul>Ecosystem Monitoring &amp; Knowledge Leadership<ul><li>Continuously survey external fraud trends, adversary techniques, tooling, and emerging threat vectors</li><li>Proactively perform threat modeling of abuse surfaces and initiate research proposals when patterns emerge</li></ul>Case Studies &amp; Reporting<ul><li>Produce clear, evidence-backed technical reports and case studies for product, engineering, operations, legal, and executive stakeholders</li><li>Document investigation workflows, attack classifications, and proof-of-concept detection logic</li><li>Drive post-incident learning by capturing lessons from fraud incidents and feeding them back into defenses</li></ul>Qualifications:<ul><li>3+ years of applied fraud experience in a high-velocity environment (fintech, consumer payments, banking, SaaS, marketplace risk, or security research)</li><li>Investigator mindset: pattern synthesis, hypothesis testing, and skilled triage between signal and noise</li><li>End-to-end investigation experience reconstructing attacker intent and behavior in multi-step attack sequences across accounts, devices, and identities</li><li>Post-containment incident response experience with a deep emphasis on post-mortems and root cause analysis</li><li>Dark and grey-web navigation and investigation experience; ability to assess source credibility and translate external intelligence into actionable insights</li><li>Strong communication: ability to explain complex, ambiguous behavior to technical and non-technical audiences</li><li>Tool fluency with data environments and investigative toolchains (BI tools, anomaly detection, case trackers)</li></ul>Preferred<ul><li>SQL for deep data querying and exploratory analysis</li><li>Python for scripting, rapid prototyping, and analytical workflows</li><li>Graph/network analysis experience to detect linked behavioral structures or actor networks</li><li>Familiarity with rule engines, signal gating, and large-scale monitoring systems</li><li>Experience applying AI tools and agents to accelerate investigations and research workflows</li><li>Ability to translate fraud research into actionable signals, rules, or labeled datasets that improve model performance</li></ul>Nice to Have<ul><li>Fraud domain certifications (e.g., CFE)</li><li>Prior work on consumer identity, payments, or risk platform development</li><li>Exposure to production ML model lifecycles and metrics for drift/decay</li><li>Experience improving internal fraud tooling, automation, or case management systems</li></ul><div> </div>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.Please review our Candidate Privacy Notice <a target="_blank" rel="noopener noreferrer ugc" href="https://plaid.com/legal/#candidate-privacy-notice">here</a>. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

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Senior Data Scientist - Network Value (Guard)

Staff Machine Learning Engineer (Research Scientist) - DFAI

Senior Data Scientist - Network Value

Senior Analytics Engineer

Senior Fraud Research Analyst

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