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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 data insights and models that improve how millions of users understand and grow their financial lives. We're looking for data scientists with experience applying state-of-the-art data analytics techniques to different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.
You’ll be a data scientist as a part of the Data organization, contributing to diverse, high-impact data insights and machine learning challenges. Specifically, you will focus on driving business impact, and production directions through data analysis and potentially help evaluate and improve ML solutions and systems. If you're interested in building state-of-the-art Data/ML solutions to unblock financial freedom for everyone, let's chat!
Responsibilities
- Applying your expertise in quantitative analysis, data mining, and data visualization to find insights for improving our API products
- Conducting large-scale A/B experiments
- Identifying useful signals that can be fed into machine learning models.
- Informing and influencing product and engineering teams through your data analysis and presentations
- Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid
- Championing a data-first approach toward decision-making across the entire organization
Qualifications
- 5+ years of industry experience in a product-focused Data Science role
- Deep familiarity with SQL and data visualization tools
- Experiencing conducting large-scale A/B experiments, analyzing results, and translating them into concrete recommendations
- Familiarity with the AWS stack
- Understanding of modern machine learning techniques, such as classification, clustering, optimization, deep neural network, and natural language processing
- Proven ability to tailor your solutions to business problems in a cross-functional team
- Ability to code and iterate independently in Python to conduct exploratory data analysis
- Experience building data pipelines in DBT or Airflow is a plus
- Bachelor's degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field
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 [email protected].
Please review our Candidate Privacy Notice here.
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
