Forward-Deployed Data Scientist II

Braze
London
Full timeFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: bachelorsSkills: ["Customer collaboration","Clear communication","Entrepreneurial problem-solving","Continuous learning","Technical guidance"]

Design and deploy end-to-end machine learning solutions that enable 1:1 personalization for leading brands. Own the full ML pipeline from customer data transformation and model training through activation, ensuring measurable customer outcomes. Provide technical guidance for successful adoption, extend Braze product capabilities for AI deployment at scale, and partner with Product to advance reinforcement learning algorithms and the BrazeAI roadmap.

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FursaFursa
Braze
Braze
2 months ago

Forward-Deployed Data Scientist II

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live
Reposted: similar role first listed 5 months ago

Job Summary

Design and deploy end-to-end machine learning solutions that enable 1:1 personalization for leading brands. Own the full ML pipeline from customer data transformation and model training through activation, ensuring measurable customer outcomes. Provide technical guidance for successful adoption, extend Braze product capabilities for AI deployment at scale, and partner with Product to advance reinforcement learning algorithms and the BrazeAI roadmap.
Location: London
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design ML use cases from the ground up by scoping solutions that optimize business value and identifying risks for successful engagements.
  • •Build and own the full ML pipeline from customer data transformation through model training and activation to personalize experiences at scale.
  • •Provide ongoing technical guidance to drive customer success, including adoption and measurable outcomes based on data science performance.
  • •Extend product capabilities by building features and tools that support the broader AI deployment effort and scale across engagements.
  • •Collaborate with the Product team to refine reinforcement learning algorithms and inform BrazeAI product strategy and roadmap using customer-facing insights.

Pay and Benefits

Perks:EquityRetirementMedicalDentalVisionLife InsuranceDisability InsurancePaid LeaveLearning BudgetEqual PaidVolunteer WeekFertility Benefits

Key Requirements

  • •Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field (required), with a Master’s or PhD preferred.
  • •3–5+ years hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments.
  • •Strong proficiency in Python (Pandas) and core ML libraries such as TensorFlow, Keras, scikit-learn, CatBoost, and XGBoost.
  • •SQL skills for querying/manipulating datasets, with experience building ML pipelines and deploying models.
  • •Experience with development best practices including modular, documented code and working practices like Git, CI/CD, testing, type-hinting, and code reviews.
Experience:3+ years
Education:Bachelor's in Computer Science, Data Science, Mathematics, Engineering, or a related field
Skills:Customer collaborationClear communicationEntrepreneurial problem-solvingContinuous learningTechnical guidance
Languages:English
Tech Stack:PythonPandasTensorFlowKerasScikit-learnCatBoostXGBoostSQLGitCI/CDTesting frameworksType-hintingCode reviewsAirflowKubernetesTerraformGCPETLReinforcement learning

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