Braze22d ago

Forward-Deployed Data Scientist II

São Paulomid

Data ScienceCustomer SupportForward

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Quick Summary

Key Responsibilities

Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup,

Technical Tools

Data ScienceCustomer SupportForward

At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.

We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.

To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.

Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.

If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.

Responsibilities

~1 min read

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

→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 BrazeAI 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

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
Experience: 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
Strong technical expertise: 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
Engineering best practices: 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 skills: experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
Customer collaborator: comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
Entrepreneurial problem-solver: you identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
Continuous learner: you stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
Clear communicator: able to explain complex technical ideas persuasively to both technical and non-technical audiences