Senior Data Scientist (AI Deployment)
Braze
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Compensation
Salary & market context
Salary not listed
- 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.
- Braze offers benefits such as: Competitive compensation that may include equity Retirement and Employee Stock Purchase Plans Flexible paid time off Comprehensive benefit plans covering medical, dental, vision, life, and disability Family services that include fertility benefits and equal paid parental leave Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend A curated in-office employee experience, designed to foster community, team connections, and innovation Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching Employee Resource Groups that provide supportive communities within Braze Collaborative, transparent, and fun culture recognized as a Great Place to Work® ABOUT BRAZE Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.™ Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses.
Requirements
Top requirements
- 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: 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
Perks & setup
Benefits candidates care about
- Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here . More details on benefits plans will be provided if you receive an offer of employment.
- From offering comprehensive benefits to fostering hybrid ways of working, we’ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as:
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
Why candidates care
Benefits & perks
- Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here . More details on benefits plans will be provided if you receive an offer of employment.
- From offering comprehensive benefits to fostering hybrid ways of working, we’ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as:
- Competitive compensation that may include equity
- Retirement and Employee Stock Purchase Plans
- Flexible paid time off
- Comprehensive benefit plans covering medical, dental, vision, life, and disability
- Family services that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
Start here
Requirements
- 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: 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
Responsibilities
What you'll do
- 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
Role snapshot
About the role
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.
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