Braze (formerly Appboy) is a customer engagement platform that delivers messaging experiences across push, email, apps, and more. Braze is built specifically for today’s mobile-first world and tomorrow’s ambient computing future. Braze is set apart as the platform that allows for real-time and continuous data streaming, replacing decades-old databases that aren’t built for today’s on-demand, always-connected customer. With data, technology, and teams working together in unison, the Braze platform makes marketing more authentic, brands more human, and customers more satisfied with every experience.
Each month, tens of billions of messages associated with over 1.5 billion active users are managed through our technology. Braze is a venture-backed company with hundreds of employees in offices located in New York City, San Francisco, London, and Singapore. We’ve been named a Leader in the Forrester Wave™: Mobile Engagement Automation Q3 2017 evaluation, recognized by Forbes Cloud 100 at #85, ranked #225 on Inc.'s 500 Fastest Growing Private Companies, and listed as #21 in the Deloitte Technology Fast 500 List. Learn more at Braze.com.
WHAT WE'RE LOOKING FOR
You love everything about data. You have no problem diving into data; cleaning it, transforming it, analyzing it, visualizing it, and using it to tell stories. You want to develop your passion into a career at a rapidly growing company with tons of data about mobile and digital interactions. You want to contribute to the business as well as grow the business.
WHAT YOU'LL DO
- Analyze billions mobile and digital messaging data points
- Be in the weeds pulling, cleaning, analyzing, and transforming raw data into insightful findings
- Build tooling for the Data Strategy Business Unit
- Build out various company-wide use cases including, but not limited to, Machine Learning use cases
WHO YOU ARE
- In-progress or recently completed BS or graduate degree in Math, Computer Science, or a Statistics-related field (e.g. econometrics, machine learning, mathematics, physics)
- Strong math, statistics, and reasoning skills
- Working knowledge of Python
- Working knowledge of relational (SQL) and/or non-relational (Mongo) databases
- Experience with ETL and/or streaming data pipelines
- Experience prototyping, refining and deploying predictive models
- Fast learner, self-starter, go-getter, intellectually curious, all that jazz
- Bonus points:
- Familiarity with columnar stores (Redshift, Snowflake or Postgres)
- Familiarity with cleaning up data for training machine learning pipelines
WHAT WE OFFER
- Daily catered lunches and fully stocked kitchen with snacks and beverages
- Collaborative, transparent, collegial and fun loving office culture
- Compensation for your hard work and many contributions
In addition, this position is non-exempt and is eligible for overtime under the provisions of the Fair Labor Standards Act.