Marketing Data Science Manager | Hybrid

Capital One

McLean (VA)

Híbrido

USD 197.000 - 225.000

Jornada completa

Hace 9 días

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

Capital One seeks a data science leader for US Card Marketing Data, focusing on personalized offers via ML models. You will collaborate with data scientists, engineers, and product managers to deliver high-value predictive solutions across channels and platforms.

You’ll build and productionize models using Python, AWS, and open‑source libraries, translating data insights into business actions that improve customer experiences and growth.

Formación

  • Bachelor's degree in a quantitative field with 6 years of analytics experience or equivalent.
  • Master's or MBA with quantitative focus plus 4 years analytics experience or PhD plus 1 year.
  • Proficiency with open-source languages and ML, and relational databases.

Responsabilidades

  • Partner with cross-functional teams to deliver data science products customers love.
  • Utilize a broad stack (Python, Conda, AWS, H2O, Spark) to extract insights from large data volumes.
  • Develop ML models from design through training, evaluation, validation, and deployment.
  • Translate complex work into tangible business objectives for stakeholders.

Educación

Bachelor's Degree in a quantitative field
Master's Degree in a quantitative field or MBA with quantitative concentration
PhD in a quantitative field
Experience leveraging open source programming languages for large scale data analytics
Experience working with machine learning
Experience utilizing relational databases

Herramientas

Python
Conda
AWS
H2O
Spark
XGBoost
scikit-learn
statsmodels

Descripción del empleo

Capital One seeks a data science leader for US Card Marketing Data, focusing on personalized offers via ML models. You will collaborate with data scientists, engineers, and product managers to deliver high-value predictive solutions across channels and platforms.

You’ll build and productionize models using Python, AWS, and open‑source libraries, translating data insights into business actions that improve customer experiences and growth.

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