Senior Field Data Scientist, AI Deployment

October 21

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Logo of Braze

Braze

Braze (Nasdaq: BRZE) is a leading comprehensive customer engagement platform that powers interactions between consumers and brands they love. With Braze, global brands can ingest and process customer data in real time, orchestrate and optimize contextually relevant, cross-channel marketing campaigns and continuously evolve their customer engagement strategies. Braze has been recognized as one of Fortune’s 2022 Best Workplaces in New York, Fortune’s 2022 Best Workplace for Millennials, and UK Best Workplaces for Women 2022 by Great Place to Work. The company is headquartered in New York with offices in Austin, Berlin, Chicago, London, San Francisco, Singapore, and Tokyo. Learn more at braze.com.

1001 - 5000 employees

💰 $80M Series E on 2018-10

📋 Description

• Collaborate with customer Analytics/BI teams and BrazeAI 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’s 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

🎯 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: 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

🏖️ Benefits

• 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®

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