Data Scientist II
The Walt Disney Company
NumpyPandasPySparkPythonScikit-LearnSparkSQL
Staff Data Scientist – Machine Learning, Credit
Plaid
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California, New York • 🇺🇸 United States
Visit company websiteSalary
💰 $253,200 - $400,000 per year
Job Level
Lead
Tech Stack
Distributed SystemsPythonSpark
About the role
- 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
Benefits
- Medical
- Dental
- Vision
- 401(k)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Machine LearningML modelsPythonSparkJupyterdata engineeringanalyticsNLP techniquesproduction environmentsbackend applications
Soft skills
collaborationownershipproject managementcross-functional teamworkcommunicationproblem-solvingprioritizationengineering decision-makingimpact quantificationfeature development
Certifications
Master’s degree in Computer ScienceMaster’s degree in MathematicsMaster’s degree in Engineeringequivalent experience
