Forward-Deployed Data Scientist, AI Deployment

Braze•Boston, MA

28d

About The Position

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. WHAT YOU'LL DO As our customer base continues to grow with the excitement around BrazeAI, we're expanding our team! Join our Field 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 OfferFit'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 WHO YOU ARE 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

Requirements

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
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
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
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
Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
You 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 Haves

Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms

Responsibilities

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 OfferFit'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

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