Senior ML & Risk Modeling Scientist

Talent Octopusventures

United States

Hybrid

USD 105,000 - 175,000

Full time

3 days ago
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Benefits offered by this job

Annual incentive bonus
Country-specific benefits

Job summary

LexisNexis Risk Solutions seeks a Sr Statistical Modeler to develop and deploy analytics and AI solutions across the modeling lifecycle. The role requires translating complex problem statements into scalable ML solutions, with independent execution and collaboration with engineering, product, and platform teams.

You’ll work with structured and unstructured data, Python/R, and cloud environments (AWS/Azure). The team emphasizes AI-forward practices and production-ready model deployment.

Qualifications

  • Advanced degree or equivalent in a related field; Master’s may substitute part of required experience.

Responsibilities

  • Applies statistical, mathematical, predictive modeling and business analysis to manage and manipulate complex data from diverse sources.
  • Develops and maintains data infrastructure linking internal datasets and creates data collection for structured/unstructured data.
  • Mentor junior staff and train team members.
  • Interpret internal/external business challenges and recommend best practices to improve products and services.
  • Collaborate with engineering, product, and platform teams to productionize models.

Skills

Data Science
Machine Learning
Python
SQL
Cloud platforms
LLM frameworks
Model deployment

Education

Master’s degree

Tools

Pandas
NumPy
scikit-learn
XGBoost
PyTorch

Job description

LexisNexis Risk Solutions seeks a Sr Statistical Modeler to develop and deploy analytics and AI solutions across the modeling lifecycle. The role requires translating complex problem statements into scalable ML solutions, with independent execution and collaboration with engineering, product, and platform teams.

You’ll work with structured and unstructured data, Python/R, and cloud environments (AWS/Azure). The team emphasizes AI-forward practices and production-ready model deployment.

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