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 (Guard)</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 Guard, 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 Guard can move top-line outcomes and influence prioritization, roadmapping, and execution across cross-functional partners. This draft follows the structure and emphasis of Plaid’s current Senior Data Scientist, Network Value posting while adapting the product context from Remember Me to Guard.<h2>Responsibilities</h2><ul><li>Champion a data-first approach to decision-making across the organization as Guard 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.The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real world production systems.As a Machine Learning Engineer on the Embedded Insights team, you will drive machine learning initiatives from concept to production, working across the full model development lifecycle. You will leverage Plaid’s unique datasets to identify high-impact opportunities for machine learning, develop proofs of concept to validate new approaches, and build MVP solutions that demonstrate customer value. Partnering closely with product managers, engineers, and other cross-functional stakeholders, you will embed within product teams to translate successful prototypes into scalable, customer-facing products. As solutions gain traction, you will help expand their reach by optimizing models for new use cases, improving system scalability, and incorporating customer feedback gathered before and after launch. You will also be responsible for maintaining and enhancing existing machine learning systems through feature development, retraining strategies, and robust monitoring frameworks, including metrics, alerts, and dashboards that ensure model performance, reliability, and long-term health.Responsibilities:<ul><li>Opportunity to shape Plaid’s future as a company where intelligence products are a core value proposition.</li><li>Dive into one of the most unique datasets available in the industry and shape the strategy to leverage its value.</li><li>Work across many different areas and learn deeply about the entire Plaid product suite</li><li>Build products that empower millions of people to achieve financial freedom and opportunity.</li><li>Work closely with customers to ensure products meet their needs and demonstrate true impact.</li><li>Join a high ownership team where the greenfield opportunity is extremely high.</li></ul>Qualifications:<ul><li>2+ years of experience in machine learning, including deploying machine learning models into real-world, customer facing systems.</li><li>Payment risk, fraud or trust &amp; safety experience.</li></ul><ul><li>High agency and creativity; experience identifying, defining, and proposing high impact machine learning opportunities.</li><li>Ability to analyze large and complex financial datasets to derive insights.</li><li>Advanced degree or equivalent work experience in Statistics, Economics, Mathematics, Data Science, or a related field.</li><li>Proficiency in SQL, Python, and data visualization/analysis tool.</li><li>Ability to clearly communicate complex technical systems and decision making.</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.

Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights

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 Embedded Insights team builds machine learning models to enable better internal decision making and to power the Plaid product suite. We are structured as a central team of MLEs and Data Scientists, and embed with partner teams to bring ML models to life.As the first Data Scientist on Plaid’s Embedded Insights team within the Data organization, you will play a foundational role in building the analytics and measurement framework that supports a broad portfolio of internal and customer-facing products. You will partner closely with product, engineering, and machine learning teams to drive data-informed decision making, evaluate product and model performance, and contribute directly to the health and growth of the Plaid network.In this role, you will analyze entities across the Plaid network to better understand behavior patterns and develop metrics and monitoring systems that identify anomalies and emerging risks. You will create dashboards and reporting frameworks that provide clear visibility into machine learning model performance, while also evaluating the impact and value of these models on both customer and internal datasets. A key part of your work will involve translating complex analyses into compelling, actionable narratives for technical and business stakeholders. You will design and analyze experiments, communicate findings across teams, and use data-driven insights to uncover opportunities to improve existing products and expand Plaid’s offerings.Responsibilities:<ul><li>Applying your expertise in quantitative analysis, data mining, and data visualization to keep the Plaid network safe and improve our product suite.</li><li>Informing and influencing product and engineering teams through your data analysis and presentations.</li><li>Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid.</li><li>Championing a data-first approach toward decision-making across the entire organization.</li></ul>Qualifications:<ul><li>5+ years of industry experience in a Data Science role.</li><li>Bachelor's degree or equivalent work experience in Computer Science, Statistics. Engineering, Economics, or a closely related field.</li><li>Experience with Payment Risk, Fraud or Trust &amp; Safety.</li><li>Deep familiarity with SQL and data visualization tools.</li><li>Understanding of modern machine learning techniques, such as classification, clustering, optimization.</li><li>Proven ability to tailor your solutions to business problems in a cross-functional team.</li><li>Ability to code and iterate independently in Python to conduct exploratory data analysis.</li><li>Experience building data pipelines in DBT or Airflow is a plus.</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 - (Payment Risk/Fraud) Embedded Insights

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.Plaid’s Data team is building models that improve how millions of users understand and grow their financial lives. We’re looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques, including natural language processing, anomaly detection, optimization, and time series forecasting, across different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.You’ll be a machine learning engineer in the Data org, contributing to diverse, high-impact machine learning challenges. In this role, you’ll focus on designing, building, and deploying scalable ML solutions and systems within the credit environment. You’ll lead experimentation with new modeling approaches and strategies, collaborate closely with engineers on ingesting signals and productionizing models, and help build the next wave of cash flow based underwriting. You’ll own AI and machine learning work across the full model lifecycle, from offline training to online serving and monitoring, while helping define the ML roadmap with cross-functional teams.<h2> Responsibilities</h2><ul><li>Build machine learning systems that empower millions of users through well-known and emerging fintech applications with access to financial services</li><li>Experiment with cutting-edge machine learning modeling techniques across high-impact credit use cases</li><li>Work on both 0-1 stage problems and scaling systems from 1-10</li><li>Develop AI and machine learning models across the full lifecycle, from offline training to online serving and monitoring</li><li>Design, build, and deploy scalable ML solutions and systems in a production environment</li><li>Collaborate with teams across Plaid to define the machine learning roadmap</li><li>Dive deep into data and apply data-driven decision-making in day-to-day work</li><li>Operate with high ownership on a bottom-up driven team</li></ul><h2> Qualifications</h2><ul><li>6+ years of experience training and serving AI and machine learning models in a production environment</li><li>Experience in fintech lending, with a strong understanding of how models are built in that space</li><li>Experience building or working with data-intensive backend applications in large distributed systems</li><li>Ability to code and iterate independently using tools such as Python, Spark, Jupyter notebooks, and standard machine learning libraries</li><li>Strong ownership mindset and a track record of driving projects to business impact</li><li>Ability to work effectively with both technical and non-technical teams</li><li>Master’s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field</li><li>Nice to have: data analytics and data engineering experience</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.

Plaid

Open jobs at Plaid

Senior Data Scientist - Network Value (Guard)

Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights

Senior Data Scientist - (Payment Risk/Fraud) Embedded Insights

Staff Machine Learning Engineer (Research Scientist) - DFAI

Senior Machine Learning Engineer - Credit

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