Braze

Senior Data Scientist

Remote
Machine Learning TensorFlow PyTorch
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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

Braze is seeking a Senior Data Scientist to join our Intelligence team. The Braze Intelligence team’s mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions.  You will help discover the scope of what is possible to improve customer engagement at scale. From that space of possibilities, you will also help select and support specific solutions as they go from prototype to product.

As a Data Scientist, you will:

  • Collaborate with Product Managers and Engineers to build innovative ways to leverage data and improve decision-making for our customers
  • Explore and analyze the billions of daily data points that Braze’s customers generate in search of predictive, valuable, actionable signals
  • Build, analyze, and iterate on models that are best suited for the job, whether that’s supervised & unsupervised learning, reinforcement learning, neural networks, or simple regressions

WHO YOU ARE

  • 5+ years of experience in the technology industry
  • 5+ years of experience working with cloud or distributed systems and large customer datasets 
  • Ph.D. in Computer Science, Applied Mathematics, or significant experience developing and deploying machine learning systems
  • Extensive experience prototyping, refining, and deploying predictive models and machine learning & AI neural networks
  • Experience working with Data Stores and frameworks such as TensorFlow and PyTorch

WHAT WE OFFER

Details of these benefits plan will be provided if a candidate receives an offer of employment. Benefits may vary by location.

From offering comprehensive benefits to fostering flexible environments, we’ve got you covered so you can prioritize work-life harmony.

  • 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 tuition reimbursement
  • Community engagement opportunities throughout the year, including an annual company wide Volunteer Week
  • 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 a leading customer engagement platform that powers lasting connections between consumers and brands they love. 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 and Singapore. We ranked #3 on Great Place to Work UK’s 2024 Best Workplaces (Large), #3 on Great Place to Work UK’s 2023 Best Workplaces for Wellbeing (Medium), #4 on Great Place to Work’s 2023 Best Workplaces in Europe (Medium), #10 on Great Place to Work UK’s 2023 Best Workplaces for Women (Large), #19 on Fortune’s 2023 Best Workplaces in New York (Large). We were also featured in Built In's 2024 Best Places to Work, U.S. News Best Technology Companies to Work For, and Great Place to Work UK’s 2023 Best Workplaces in Tech.

You’ll find many of us at headquarters in New York City or around the world in Austin, Berlin, Chicago, Jakarta, London, Paris, San Francisco, Singapore, 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.

Braze
Braze
Analytics CRM Marketing Marketing Automation Software

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