Senior Forward-Deployed Data Scientist, AI Deployment at Braze

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Feb, 26

Salary

148500.0

Posted On

18 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Pandas, TensorFlow, Keras, Scikit-Learn, CatBoost, XGBoost, SQL, Machine Learning, Data Integration, ETL, Reinforcement Learning, DevOps, Collaboration, Problem-Solving, Communication

Industry

Software Development

Description

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 For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $$133,700-148,500/year with an expected On Target Earnings (OTE) between $148,500-165,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, Braze offers full- and part- time employees a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that all Braze employees own a piece of our company. WHAT WE OFFER 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 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 allows any marketer to collect and take action on any amount of data from any source, so they can creatively engage with customers in real time, across channels from one platform. From cross-channel messaging and journey orchestration to Al-powered experimentation and optimization, Braze enables companies to build and maintain absolutely engaging relationships with their customers that foster growth and loyalty. Braze is proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore. In 2025, we were recognized as one of Built In’s Best Places to Work. In 2024, we were included in U.S. News & World Report’s Best Companies to Work For (Top 10%) and recognized in Great Place to Work’s Fortune Best Medium Workplaces, Fortune Best Workplaces in Technology, Fortune Best Workplaces for Parents, and Fortune Best Workplaces for Women. Additionally, we were featured in Great Place to Work UK’s Best Workplaces, Best Workplaces in Europe, Best Workplaces for Development, Best Workplaces for Wellbeing, Best Workplaces for Women, and Best Workplaces in Technology. You’ll find many of us at headquarters in New York City or around the world in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, Singapore, São Paulo, Seoul, Sydney and Tokyo – not to mention our employees in nearly 50 remote locations. BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER At Braze, we strive to create equitable growth and opportunities inside and outside the organization. Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're 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. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you. We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we’d love to meet you. Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.

Responsibilities

Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration. Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success.