Senior Data Scientist

Zip Co

. Develop advanced modeling solutions for Zip’s next generation of financial products using rich data sources such as bank transaction data .

Posted 11/3/2026full-timeRemote • United StatesSenior💰 $162,000 - $203,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing advanced AI and machine learning models for financial products, leveraging strong analytical skills and experience with relevant data sources. Proficient in Python, SQL, and data science methodologies, with a focus on risk mitigation and profitable growth.

Highest-signal resume keywords

Advanced Degree In Quantitative Field5+ Years Of Experience In Data ScienceProficiency In Python And SQLExperience With Neural Networks And GenAIFamiliarity With Financial Services Data

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAI ModelingProbabilityStatisticsApplied Research MethodsData AnalysisModel EvaluationRisk MitigationCashflow Data AnalysisModel Scalability

Soft Skills

Problem-SolvingSelf-Starter MentalityIndependent WorkCommunication SkillsAbility To Thrive In Fast-Paced Environment

Tools & Technologies

PythonSQLSparkPySparkGitPlaidMXFinicity

Industry Keywords

Financial ServicesData ScienceCredit RiskFraud RiskMachine Learning Engineering

Tech Stack

Tools & technologies

PySparkPythonSparkSQL

About the role

Key responsibilities & impact

Develop advanced modeling solutions for Zip’s next generation of financial products using rich data sources such as bank transaction data
Develop and experiment with traditional machine learning, algorithmic, and AI-centric modeling approaches
Independently design, build, evaluate, and iterate on AI/ML models
Rapidly experiment and build realistic proofs of concept
Assist with test designs producing data for future model versions
Balance short-term business outcomes with longer-term experimental opportunities
Use AI to improve model quality, analytical efficiency, or product outcomes
Build models mitigating risk while driving profitable growth
Collaborate with Data and Machine Learning Engineering teams on data availability and model scalability
Own modeling solutions end-to-end, from development through production monitoring
Communicate findings, recommendations, and tradeoffs to business stakeholders

Requirements

What you’ll need

Advanced degree in a quantitative field (e.g., Mathematics, Physics, Social Science, Computer Science); PhD preferred
5+ years of experience in Data Science, which can include PhD work
2+ years of experience working with data relevant to Financial Services
Self-starter mentality with strong problem-solving and research skills; ability to work independently
Solid grasp of probability, statistics, and applied research methods
Experience working with cashflow data (e.g., Plaid, MX, Finicity) highly preferred
Proficiency in Python and SQL; hands-on experience with Spark/PySpark a plus
Experience with Neural Networks, LLMs, and GenAI
Experience with credit and/or fraud risk a plus
Familiarity with version control systems such as Git
Ability to thrive in a fast-paced, multi-tasking environment
Visa sponsorship is not available for this position

Benefits

Comp & perks

Flexible working culture
Incentive programs
Unlimited PTO
Generous paid parental leave
Leading family support policies
Company-sponsored 401k match
Learning and wellness subscription stipend
Beautiful Union Square office with a casual dress code
Industry-leading, employer-sponsored insurance for you and your dependents, with several 100% Zip-covered choices available
Potential bonus and/or commission awards
Medical, financial, and other benefits