Ever had your credit or debit card stolen? It happens to millions of consumers at the merchants they shop at every day. Which is why we built Rippleshot. We detect the data breaches that cause these problems faster than anyone else in the market. This allows banks, credit unions and merchants to act on the breaches quicker and smarter than ever before — which means consumers are alerted earlier.
Six years ago, we were the new kids on the block. Today, dozens of banks, credit unions, and billion-dollar companies trust us to help them fight fraud. Always smarter, always faster. And we are not done. The fraudsters are good. We need to be better.
Rippleshot brings the power of machine learning and big data to help banks and credit unions reduce fraud by analyzing millions of card transactions daily to proactively detect compromised merchants and identify an issuer’s at-risk cards.
Who We Are:
We’re an eclectic mixture of data scientists, former journalists, finance analysts and seasoned entrepreneurs who all share a passion for mission-driven work. Well…and food. We definitely love food here. But we digress.
Data breaches are more than just a headline you read in the news every day. They’re causing billion-dollar losses to merchants, financial institutions, insurers, consumers and everyone in between. At its core, Rippleshot is a tool to catch them earlier - and it’s gotten us quite a bit of attention. We’ve won innovation awards locally and globally.
That’s just the tip of the spear. We believe a tsunami of fraud is headed our way over the next five years. We think we have the winning combination of analytics, machine learning, big data, and people to protect our clients from these evolving threats. It’s a race and we are all in!
What We Need:
Rippleshot is seeking a Data Engineer to architect, build, scale, and maintain a world-class analytics and machine-learning infrastructure. We are seeking a qualified individual who is eager to ensure that our ability to store, process, and analyze data keeps up with our user growth and our ambitions. You would be an early hire in a fast growing startup and would have significant impact in the design and implementation of the engineering vision as our company and team grows.
This job also involves the following responsibilities:
- Work with a team of data scientists and engineers to build, improve, and maintain a machine learning infrastructure designed for predictive analytics and modeling
- Design, build, and maintain processes and components of a streaming data/ETL pipeline, from datastore layout and SQL queries to large batch processing jobs, MapReduce frameworks, and data warehouse / cloud storage
- Focus on data quality - detect data/analytics quality issues all the way down to root cause, and implement fixes and data audits to prevent/capture such issues
- Integrate data sources, including interacting with APIs, create and maintain data schemas, and store data in our datastores
You’ll Be a Great Fit If:
You are passionate about data! You’re smart enough to work just about anywhere, but you’re picky about finding the right role. You’re experienced, but you love to learn, and you want to work with other smart people like you who want to have fun building something great.
You must meet all of these qualifications:
- Strong experience with structured/semi-structured data at large (2+ years),
- Working knowledge of relational database schema design and performance tuning (2+ years),
- Experience with NoSQL technologies like Hadoop, MapReduce, and Spark (2+ years),
- Strong Object Oriented Programming experience, preferably Python (2+ years),
- At least one scripting language in a Linux environment, preferably Python (2+ years),
- Rigor in A/B testing, automated testing, and other engineering best practices