Braze

1 month ago

Forward-Deployed Data Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Develop and deploy end-to-end ML solutions for 1-to-1 personalization at Braze. Design RL use cases, build and own full ML pipelines from data transformation to model activation, and provide ongoing technical guidance to customers. Collaborate with product to advance BrazeAI, extend platform capabilities, and shape the BrazeAI roadmap with deep technical and customer-facing insights.

Location: Tokyo

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design RL use cases from the ground up, scoping solutions that optimize for real business value and identify risks to ensure successful engagements.
•Build and own the full ML pipeline—from raw data transformation to model training and activation—to deliver personalized experiences for millions of end users.
•Provide ongoing technical guidance to customers to ensure data science performance, successful adoption, and measurable outcomes.
•Extend product capabilities by developing features and tools that support the broader AI deployment team and scale solutions across engagements.
•Partner with the Product team to refine Braze’s reinforcement learning algorithms and advance BrazeAI capabilities.

Pay and Benefits

Equity and Bonus:Equity

Perks:EquityLearning Budget

Key Requirements

•Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field; Master’s/PhD preferred
•3–5+ years hands-on data science or ML engineering experience
•Proficiency in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost); strong SQL skills
•Experience deploying ML pipelines and models in production environments; solid software development practices (Git, CI/CD, testing, typing)
•Nice-to-have: DevOps tools (Airflow, Kubernetes, Terraform, GCP) and RL algorithms

Experience:3-5 yearsData ScienceMachine LearningProduction MLReinforcement Learning

Education:Bachelor's

Skills:PythonPandasTensorFlowKerasScikit-learnCatBoostXGBoostSQLGitCI/CDTestingTypingAirflowKubernetesTerraformGCP

Languages:English

Tech Stack:PythonTensorFlowKerasScikit-learnCatBoostXGBoostSQLGitCI/CDAirflowKubernetesTerraformGCP

Company Brief

Braze

Provides a customer engagement platform that helps brands create personalized messaging and lifecycle campaigns across mobile, web, email, and other channels to drive retention, engagement, and revenue.

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 100M to 250M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 2011

Website LinkedIn

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Braze

1 month ago

Forward-Deployed Data Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Tokyo

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design RL use cases from the ground up, scoping solutions that optimize for real business value and identify risks to ensure successful engagements.
•Build and own the full ML pipeline—from raw data transformation to model training and activation—to deliver personalized experiences for millions of end users.
•Provide ongoing technical guidance to customers to ensure data science performance, successful adoption, and measurable outcomes.
•Extend product capabilities by developing features and tools that support the broader AI deployment team and scale solutions across engagements.
•Partner with the Product team to refine Braze’s reinforcement learning algorithms and advance BrazeAI capabilities.

Pay and Benefits

Equity and Bonus:Equity

Perks:EquityLearning Budget

Key Requirements

•Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field; Master’s/PhD preferred
•3–5+ years hands-on data science or ML engineering experience
•Proficiency in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost); strong SQL skills
•Experience deploying ML pipelines and models in production environments; solid software development practices (Git, CI/CD, testing, typing)
•Nice-to-have: DevOps tools (Airflow, Kubernetes, Terraform, GCP) and RL algorithms

Experience:3-5 yearsData ScienceMachine LearningProduction MLReinforcement Learning

Education:Bachelor's

Skills:PythonPandasTensorFlowKerasScikit-learnCatBoostXGBoostSQLGitCI/CDTestingTypingAirflowKubernetesTerraformGCP

Languages:English

Tech Stack:PythonTensorFlowKerasScikit-learnCatBoostXGBoostSQLGitCI/CDAirflowKubernetesTerraformGCP

Company Brief

Braze

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 100M to 250M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 2011

Website LinkedIn