✦ Luna Orbit — Data & Analytics

Forward-Deployed Data Scientist

at Braze

📍 New York City Onsite Posted March 19, 2026
Type Full-Time
Experience mid
Exp. Years 3-5+ years
Education 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
Category Data & Analytics

This role involves developing and deploying machine learning models, working with large datasets, and collaborating with customer teams to ensure successful implementation of AI solutions.

  • Collaborate with customer analytics teams
  • Develop reusable data pipelines
  • Refine reinforcement learning algorithms
  • Shape product strategy with insights
  • Ensure successful adoption and outcomes

Stack includes Python, Pandas, TensorFlow, Keras, scikit-learn, SQL, and ML pipelines, with deployment and collaboration tools like Git, CI/CD, and cloud platforms.

The ideal candidate is a mid-level data scientist with 3+ years of experience working with large-scale data, proficient in Python and machine learning libraries, and experienced in deploying models in production environments.

PythonPandasSQLML pipelinesmodel deployment
DevOps toolsAirflowKubernetesTerraformGCP
GitCI/CDTensorFlowKerasscikit-learnXGBoostCatBoostAirflowKubernetesTerraformGCP
PythonPandasTensorFlowKerasscikit-learnCatBoostXGBoostSQLML pipelinesmodel deploymentGitCI/CDtesting frameworkstype-hinting
PythonPandasTensorFlowKerasscikit-learnCatBoostXGBoostSQLML pipelinesmodel deploymentGitCI/CDtesting frameworkstype-hinting
collaborationcommunicationautonomyaccountabilityproblem-solvingadaptability
Industry SaaS
Job Function Developing and deploying machine learning models in a customer-facing environment
Role Subtype Data Scientist
Tech Domains Python, TensorFlow, Keras, scikit-learn, SQL / PostgreSQL
Data ScientistPythonPandasTensorFlowKerasscikit-learnCatBoostXGBoostSQLML pipelinesmodel deploymentGitCI/CDtesting frameworkstype-hintingmachine learninglarge-scale dataproduction environmentscollaborationcommunicationautonomyaccountabilityproblem-solving

Lack of Python or SQL experience, No experience with ML pipelines or deployment, Less than 3 years of experience, No relevant technical degree

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