Senior Statistical Modeler - Remote US AI/ML Leader

LexisNexis Special Services Inc.

United States

Remote

USD 105.000 - 175.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

LexisNexis Special Services Inc. seeks a Sr Statistical Modeler to translate complex business problems into scalable ML solutions across the full modeling lifecycle.

This remote, nationwide role collaborates with engineering, product, and data teams to deploy analytics in production and to communicate insights to non-technical stakeholders. Candidates should have advanced data science credentials, hands-on ML experience, and proficiency with Python or R, SQL, and cloud platforms.

Qualifikationen

  • Proven Data Science experience with advanced academic credentials; Master’s degree may substitute part of the experience.
  • Hands-on experience applying ML and statistical techniques to real-world problems.
  • Experience with structured/unstructured data at scale and cloud platforms.

Aufgaben

  • Applies statistical, mathematical, predictive modeling, and business analysis skills to manage complex data.
  • Develops data infrastructure and data collection frameworks for varied data sources.
  • Trains, evaluates, and maintains ML models and communicates results to stakeholders.
  • Mentors junior staff and helps productionize models.

Kenntnisse

Data Science
Machine Learning
Python
R
SQL
AWS
Azure
LLM frameworks
Model deployment
Communication skills

Ausbildung

Master’s degree in a related discipline

Tools

pandas
NumPy
scikit-learn
XGBoost
PyTorch

Jobbeschreibung

LexisNexis Special Services Inc. seeks a Sr Statistical Modeler to translate complex business problems into scalable ML solutions across the full modeling lifecycle.

This remote, nationwide role collaborates with engineering, product, and data teams to deploy analytics in production and to communicate insights to non-technical stakeholders. Candidates should have advanced data science credentials, hands-on ML experience, and proficiency with Python or R, SQL, and cloud platforms.

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