Braze is hiring a Field Data Scientist, AI Deployment to partner directly with customers to ensure their success with BrazeAI. You will collaborate on implementations, extend product capabilities, refine algorithms, and contribute to product strategy.
What You'll Do
- 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 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.
What We're Looking For
- Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
- 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.
- 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.
- 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.
- Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value.
- Identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions.
- Stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow.
- Able to explain complex technical ideas persuasively to both technical and non-technical audiences.
Nice to Have
- Master’s or PhD in a relevant technical discipline.
- Experience in customer-facing or consulting roles.
- Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms.
Technical Stack
- Python, Pandas
- TensorFlow, Keras, scikit-learn, CatBoost, XGBoost
- SQL
- Git, CI/CD
- Airflow, Kubernetes, Terraform, GCP
Team & Environment
You'll be part of the Field Data Scientist group.
Benefits & Compensation
- Compensation: $133,700-$148,500/year + equity grants of restricted stock (RSUs).
- 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.
Work Mode
This role is based in New York City.
Braze is an equal opportunity employer committed to offering all candidates a fair, accessible, and inclusive experience – regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran.
