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Forward-Deployed Data Scientist, AI Deployment

United States, New York City 145800.00 USD / Year · Job Posted December 28, 2025
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Job Description

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Field Data Scientist group of creative technical experts who partner with customers to ensure their success.

Job Responsibility

  • Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
  • Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
  • Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
  • Contribute to shaping OfferFit’s product strategy and roadmap through customer-facing insights and technical expertise
  • Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required
  • Master’s or PhD in a relevant technical discipline preferred
  • 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments
  • Experience in customer-facing or consulting roles is strongly preferred
  • Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost)
  • Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
  • You write well-structured, modular, documented code
  • follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews)
  • and can build scalable, maintainable solutions

Nice to have

Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms

What we offer

  • Competitive compensation that may include equity
  • Retirement and Employee Stock Purchase Plans
  • Flexible paid time off
  • Comprehensive benefit plans covering medical, dental, vision, life, and disability
  • Family services that include fertility benefits and equal paid parental leave
  • Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
  • A curated in-office employee experience, designed to foster community, team connections, and innovation
  • Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
  • Employee Resource Groups that provide supportive communities within Braze

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