Forward-Deployed Data Scientist

Braze
Tokyo
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: bachelorsSkills: ["Autonomy","Accountability","Collaboration","Communication","Problem-solving"]

Design and deploy reinforcement learning solutions that improve business outcomes across complex marketing journeys. Build and own end-to-end ML pipelines—from raw customer data through transformation, training, and activation—to power 1:1 personalization at scale. Work closely with customers for technical guidance, adoption, and measurable results, while partnering with product to advance reinforcement learning algorithms and contribute to the BrazeAI strategy and roadmap.

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FursaFursa
Braze
Braze
2 months ago

Forward-Deployed Data Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Design and deploy reinforcement learning solutions that improve business outcomes across complex marketing journeys. Build and own end-to-end ML pipelines—from raw customer data through transformation, training, and activation—to power 1:1 personalization at scale. Work closely with customers for technical guidance, adoption, and measurable results, while partnering with product to advance reinforcement learning algorithms and contribute to the BrazeAI strategy and roadmap.
Location: Tokyo
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design reinforcement learning use cases from the ground up, optimizing for business value and proactively identifying risks across marketing journeys.
  • •Build and own end-to-end ML pipelines, transforming customer data, training models, and activating decisions to personalize experiences for millions.
  • •Provide ongoing technical guidance to drive customer success, ensuring performance, adoption, and measurable outcomes.
  • •Extend AI deployment capabilities by developing features and tools that scale across engagements.
  • •Partner with product teams to refine reinforcement learning algorithms and shape BrazeAI product strategy and roadmap with customer-facing insights.

Pay and Benefits

Equity and Bonus:Equity
Perks:EquityRetirementPaid LeaveHealth InsuranceDentalVisionLife InsuranceDisability InsuranceLearning Budget

Key Requirements

  • •Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field (Master’s or PhD preferred).
  • •3–5+ years hands-on experience as a Data Scientist, Machine Learning Engineer, or similar in large-scale data and production environments.
  • •Strong ML and data skills, including Python (Pandas), ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost), and SQL.
  • •Experience building production ML pipelines and deploying models, with strong engineering practices (modular, documented code; Git/CI-CD/testing; code reviews; type-hinting).
  • •Nice-to-have: DevOps tools (Airflow, Kubernetes, Terraform, GCP) and/or reinforcement learning experience; comfortable working with clients and cross-functional teams.
Experience:3+ yearsMachine learningReinforcement learningProduction environmentsCustomer-facingMarketing technology
Education:Bachelor's in Computer Science, Data Science, Mathematics, Engineering, or a related field
Skills:AutonomyAccountabilityCollaborationCommunicationProblem-solving
Languages:Japanese
Tech Stack:PythonPandasTensorFlowKerasScikit-learnCatBoostXGBoostSQLGitCI/CDTesting frameworksType-hintingAirflowKubernetesTerraformGCP

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
WebsiteLinkedIn