Hands-on develop, productionize, and operate Machine Learning models and pipelines to improve a diverse range of Plaid products.
Continuously proposing and developing new features to improve the AI/ML model performance.
Working with the ML infrastructure team to improve ML infrastructure that powers the end-to-end ML development lifecycle.
Debugging ML production issues and ensuring stable model serving.
Work collaboratively with cross-functional partners to identify opportunities for business impact, understand, refine, and prioritize requirements for AI/ML models, drive engineering decisions, and quantify impact.
Requirements
8+ years of experience developing, training, and deploying ML models in production environments
Proven experience building and maintaining data-intensive backend applications within large, distributed systems
Strong programming skills in Python and familiarity with tools such as Spark, Jupyter, and standard ML libraries
Background in fintech or other data-rich, regulated domains
Demonstrated ability to take ownership and drive projects from concept to measurable business impact
Solid understanding of data engineering and analytics concepts
Skilled at collaborating across technical and non-technical teams
Master’s degree (or equivalent experience) in Computer Science, Mathematics, Engineering, or a related field
Nice to Have: Hands-on experience with data engineering or analytics tooling
Nice to Have: Experience applying NLP techniques in production systems
Analyst within Credit Risk Management team identifying credit segmentation opportunities using statistical methods. Collaborating with teams to enhance credit decision process and policies.
Data Manager managing and analyzing company data at Amoddex, a consultancy for IT transformation projects. Ensuring data integrity and supporting strategic decision - making in a collaborative environment.
Data Scientist at Capital One on the LLM Customization Team utilizing the latest in computing and machine learning technologies. Collaborating with data scientists and engineers to deliver AI powered products.
Lead Full Stack Data Scientist at Tilt, building the intelligence layer for data - based decisions. Driving data science strategy and analytics to enhance product and growth insights.
Data Scientist focusing on Generative AI applications and engineering problem - solving at Ford. Collaborating with cross - functional teams to innovate and improve technology solutions in the automotive sector.
AI Engineer/Data Scientist in Ford's Global Data Insights & Analytics team. Developing advanced AI/ML solutions and collaborating on cloud - native data products.
Data Scientist transforming customer data into insights that guide strategic decisions for Riachuelo. Collaborating with teams to analyze and visualize data trends for business growth.
VP, Credit Risk & Data Science overseeing credit risk framework and portfolio management at Purpose Financial. Leading strategy and governance to enable profitable growth and risk mitigation.
Data Scientist joining a leading economic consultancy to implement data science solutions for business challenges and advance thought leadership in advanced analytics.