Data Scientist - Monitoring & Anomaly Detection Platform - Uber
- Data Scientist
- Data Engineer
- Data Analytics
Uber is a technology company that is changing the way the world thinks about transportation. We are building technology people use everyday. Whether it's heading home from work, getting a meal delivered from a favorite restaurant, or a way to earn extra income, Uber is becoming part of the fabric of daily life.
We're making cities safer, smarter, and more connected. And we're doing it at a global scale-energizing local economies and bringing opportunity to millions of people around the world.
Uber's positive impact is tangible in the communities we operate in, and that drives us to keep moving forward.
For Uber to be a world-class transportation option for everyone, it must be one thing first - Reliable. The Monitoring Platform is about bringing world-class thinking around anomaly detection, trace analysis, root cause detection, and machine learning on a large scale to help create technology to guarantee that the Uber experience is always excellent.
What You'll Do
- Working on a cross functional team of data scientists and engineers to support Uber's existing anomaly detection algorithms and developing new anomaly detection functionality.
- Create and own data models around Uber's outages - what information should we be capturing to analyze the cause of an outage when it's happening? What information needs to be captured to predict and prevent a similar outage in the future?
- Engage with on-duty engineering and business rotations to help the monitoring team improve product market fit.
- Create technology to allow teams to have a "self service" point of view around monitoring their products while simultaneously allowing the platform the collect information to develop more and more intelligent tools.
What You'll Need
- A graduate degree or equivalent in computer science or a quantitative domain plus hands-on software engineering and data science experience. Technical understanding must go from the highest abstractions down to the metal.
- At least 4 years experience delivering, scaling, and owning highly successful and innovative data science products with your fingerprints all over them - you're extremely proud of what you've accomplished.
- Demonstrable proficiency in producing production level code (Python, Go, Spark preferred) and programming concepts, combined with the enthusiasm and passion to build.
- An ability to connect the deep domain expertise of the researcher with the pragmatism and intuition of the entrepreneur - you're a true generalist.
- Demonstrable domain expertise in time series modeling, anomaly detection, signal processing, machine learning, failure analysis, or outlier detection methods.
- A high bar across the board - from your own contributions to the people you work with to the products you work on.
- A "driver" personality - biased toward action, great collaborator and master disambiguator / simplifier - constantly pushing toward clarity and delivery.
- Grittiness. You never hesitate to roll up your sleeves and address something hands-on, you persevere when others fall away.
- Finger-tippiness with data: you just go get the data you need with no muss / fuss and can whip it into an insightful story with no help. You know how to leverage data to make decisions without getting stuck in paralysis by analysis.
- Employees are given Uber credits every month.
- The rare opportunity to change the way the world moves. We're not just another social web app, we're moving real people and assets and reinventing transportation and logistics globally.
- Smart, engaged co-workers.
- 401(k) plan, gym reimbursement, nine paid company holidays.
- Full medical/dental/vision package to fit your needs.
- Unlimited vacation policy; take time when you need it.
Be sure to check out the Uber Engineering Blog to learn more about the team.
Uber is an equal opportunity employer and enthusiastically encourages people from a wide variety of backgrounds and experiences to apply. Uber does not discriminate on the basis of race, color, religion, sex (including pregnancy), gender, national origin, citizenship, age, mental or physical disability, veteran status, marital status, sexual orientation or any other basis prohibited by law.
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