Data Scientist - ML Payment Risk
San Francisco
Plaid Inc.
Plaid helps companies build fintech solutions by making it easy, safe and reliable for people to connect their financial data to apps and services.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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Classification Computer Science Economics Engineering Feature engineering Fraud risk Jupyter Machine Learning ML models NLP Python Spark Statistics
Perks/benefits: Career development Health care
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