Experienced Data Scientist ML Payment Risk

We believe 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 infrastructure developers need 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 and 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 11,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Salt Lake City, Washington D.C., London and Amsterdam.

Plaid's data science team is building 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 machine learning and modeling techniques -- including natural language processing, anomaly detection, optimization, and time series forecasting -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You'll be a data scientist embedded on the Payment Risk team, working on financial and fraud risk assessment for payment ACH transactions. In this position, you will help build an industry-leading and customer-facing transaction risk engine. Specifically, you will focus on improvements to model performance, feature engineering, stability, and coverage. You will lead the efforts to experiment with new modeling approaches and strategies, as well as integrate third-party data. You'll be collaborating closely with a skilled team of engineers on ingesting signals and productionizing these models, as well as directly interacting with our customers in this process.If you're interested in building state of art ML solutions to power payment financial and fraud risk management, let's chat!

We're guided by our principles including impact, growing together, embracing openness and positivity, and inventing tomorrow; we're looking for leaders who are motivated by those same principles.

What excites you...

• Building an industry-defining transaction risk model, using Plaid's rich data network across 13,000 financial institutions and 7000 apps.
• Opportunity to fundamentally impact how consumers interact with their financial apps by developing new model approaches and frameworks
• Be the ninja of all things Machine Learning by using Plaid's state of the art systems and utilizing features of billions of transactions to drive new models
• Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid
• Internal and external visibility: Championing a data-first approach toward decision-making across the entire organization.
• Tons of growth: The team is growing quickly and you will have the opportunity to grow, and mentor other data scientists as we scale the team
• Helps build the next $1B+ business for Plaid
• What excites us...
• 5+ years of industry experience developing machine learning models from inception to business impact. Proven ability to tailor your solutions to business problems in a cross-functional team
• Deep understanding of modern machine learning techniques and their mathematical models, such as classification, clustering, optimization, deep neural network, and natural language processing
• Ability to code and iterate independently on top of data infrastructure tools like Python, Spark, Jupyter notebooks, standard ML libraries, etc
• Strong product intuition, and excitement to work fast and iterativelyData analytics and data engineering experience are a plus
• Bachelor's degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field
• 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.
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