Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Forward Deployed Data Scientist, AI Deployment

Braze
London
1 day ago
Create job alert

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 Braze'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

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.

Benefits

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 helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI™ allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences.

The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 “Best of Marketing and Digital Advertising Software Product” in 2025.

Braze was also named a 2025 Best Companies To Work For by U.S. News & World Report, a 2025 America’s Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology™ by Great Place To Work®, among other accolades. Braze is also proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore.

The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo.

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.

Related Jobs

View all jobs

Senior Forward Deployed Data Scientist, AI Deployment

Principal Data Scientist

Data Architect

Data Engineering Lead — Azure & Databricks (Remote)

Remote Head of Data Engineering - Azure & Databricks

Remote Data Engineering Lead - Azure & Databricks

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.