Data Scientist
Redwood City, California, United States
Applications have closed
Miles is a universal rewards app empowering anyone to earn miles automatically for all forms of travel and commute. You can then redeem your miles from amazing brands such as HP, Garmin, Pandora, Chewy, Home Chef, Buffalo Wild Wings, Wayfair, Sam’s Club, and many more.
Similar to a frequent flyer program, but for all forms of transportation, Miles delivers value for every mile traveled, across every mode of travel, anywhere in the world. Whether by car (as a driver, passenger, or rideshare), plane, train, subway, bus, boat, bicycle, or on foot, the Miles app effortlessly awards users’ travel - regardless of where their journey takes them. Miles can be saved or redeemed at any time - with the value increasing every month as more merchants accept them as a form of payment.
Miles is a Silicon Valley-based startup with backing from prominent VCs (Porsche, Scrum, Panasonic, and Urban.us). Join the Miles family and be part of this revolutionary program!
Miles Engineering
You will be working with a great team from diverse backgrounds in a collaborative and supportive environment. We solve a wide variety of interesting technical challenges and continually build up our platform to power the next generation of scale and features. We partner closely with Product, Design, and UX teams to build and ship the most impactful.
You want to join an early startup on a fast growth trajectory. You are self-motivated, take end-to-end ownership, communicate effectively, and are a fast learner.
Responsibilities
- Productionize, launch, and monitor predictive models with high-dimensional, fast-moving real-time datasets.
- Design, analyze, and manage both simulated and live experiments (A/B and multivariate tests) to drive KPI improvements.
- Lead end-to-end cross functional analytics projects: scope requirements with stakeholders, collect and analyze data, as well as summarize and present key insights in support of critical decision making.
- Analysis of large amounts of data to gather insights, identify trends, detect anomalies, develop key KPIs, and feed powerful dashboards and visualizations.
- Build new and improve existing ML models by incorporating new sources, developing and testing model improvements, running experiments, and fine tuning parameters.
Requirements
- MS degree in a quantitative field such as Machine Learning, Data Science, Statistics, Applied Mathematics, or Physics, or a BS Degree with 2+ years of full-time experience.
- Experience with data analysis and statistical modeling using Python packages such as pandas, scipy, statsmodels, scikit-learn, etc.
- Communicate key data insights & recommendations to technical & non-technical stakeholders using visualizations.
- Expertise with querying data (SQL, Redshift, Spark) and analyzing millions to billions of rows of data points.
- Experience building machine learning, statistical and analytical models, and tuning parameters to solve practical business problems.
- Experience designing experiments, extracting insights, and writing testable code.
Bonus points
- You have worked extensively with geospatial data at scale.
- Prior experience in handling large datasets (billion+)
- Specialization in spatiotemporal clustering in the presence of noise.
- Prior startup experience.
- Ph.D. degree.
Benefits
- Competitive salary based on experience
- Opportunity to create impact in a high-growth startup environment
- 401K program with company matching to help you invest in your future
- Employee healthcare benefits include medical, dental, vision insurance
- Paid time off + sick days
- Work-from-home Fridays
- Wellness Day - One additional holiday each month for employee wellness
- Employee Referral bonus
- Daily office meals and a fully stocked kitchen
- Monthly team-building activities and happy hours
- Stock in an early-stage, fast-growing startup company
Our Commitment to Inclusivity and Diversity
Miles is committed to creating an inclusive and diverse environment where people of every background can thrive and feel welcome. We consider applicants without regard to race, color, creed, religion, national origin, genetic information, gender identity or expression, sexual orientation, pregnancy, age, marital, veteran, or physical or mental disability status.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Clustering Data analysis Engineering KPIs Machine Learning Mathematics ML models Pandas Physics Python Redshift Scikit-learn SciPy Scrum Spark SQL Statistical modeling Statistics statsmodels Testing UX
Perks/benefits: Career development Competitive pay Health care Insurance Salary bonus Snacks / Drinks Startup environment Team events
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