Ocrolus

Senior Data Scientist

Ocrolus

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇺🇸 United States

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Salary

💰 $150,000 per year

Job Level

Senior

Tech Stack

AWSCloudGRPCPandasPostgresPythonScikit-LearnShell ScriptingSQL

About the role

  • Partner with Product, Engineering, and other stakeholders to translate ambiguous business challenges into well-defined data science problems
  • Own the end-to-end lifecycle of data science models, from data exploration and feature engineering to deployment, monitoring, and continuous improvement in production
  • Develop robust, scalable, and efficient models, thoughtfully balancing algorithmic complexity against interpretability, business needs, and delivery timelines
  • Examples of data science initiatives include: using NLP/LLMs to classify transactions into standardized categories, training gradient boosting trees to predict loan default probability and loss-given-default based on transactional data, and building an entity resolution system to match financial documents across time with a specific borrower

Requirements

  • 5+ years of professional experience building and deploying machine learning models in a production environment
  • Lending domain experience, applying data science principles in the management of portfolio risk or acquisition.
  • Bachelor’s or Master’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Finance, Math, Engineering)
  • Full stack data-science experience: ideating, building, deploying, monitoring, and maintaining production ML models that solve product needs and perform with high levels of accuracy, stability, and coverage
  • The ability to communicate and present complex technical topics and results to various audiences
  • Passion for understanding the “why” of the problem and the impact of solutions on client outcomes
  • Deep understanding of statistics, probability, and machine learning algorithms
  • Strong software engineering and data engineering fundamentals
  • Expert-level programming skills in Python and proficiency with core data science libraries (e.g., pandas, scikit-learn, Hugging Face)
  • Excellent SQL skills and comfort working with large and complex data warehouses (Snowflake/Postgres)
  • Experience with CI/CD, shell scripting, Git/version control, REST/GRPC APIs, and cloud infrastructure (AWS: S3, EKS, etc)
Benefits
  • equity
  • benefits 📊 Resume Score Upload your resume to see if it passes auto-rejection tools used by recruiters Check Resume Score

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningdata explorationfeature engineeringNLPgradient boostingstatisticsprobabilityPythonSQLdata science
Soft skills
communicationpresentationproblem-solvingclient outcomes understanding
Certifications
Bachelor's degreeMaster's degree