Data Scientist at CLEAR
CLEAR’s mission is to strengthen security and create frictionless experiences for consumers. We believe you are you and by using your biometrics - your fingerprints, eyes, and face - we keep you moving. Imagine a world where you can do virtually everything you need to – breeze through the airport, buy a beer at the game, check-in at the doctor’s office, access your office building, and more – without ever pulling out your wallet or phone. Now in 60+ airports and other venues nationwide, you are your ID, credit card, ticket, reservation and more with CLEAR.
We’re defining and leading an entirely new industry, obsessing over our customers, and investing in great people to lead the way. Recently named on CNBC’s Disruptor 50 List and winner of the SXSW Interactive Innovation Award, we're working tirelessly to create frictionless customer experiences for our 4+ million members across the country.
We’re seeking an innovative and results-oriented Data Scientist to identify actionable insights throughout our business. As a critical member of our insights and analytics team, you will have a prominent voice in the future of our company. You’re a deep thinker who is intellectually curious and enjoys solving critical problems. You are a self starter who can own a solution from end to end.
You are technically proficient and have the ability to access and wrangle large amounts of structured and unstructured data, a great business sense, the desire to influence strategic decisions with data-driven analysis. You think deep, you happily prove your assumptions and you work fast. Lastly, you have strong written and verbal communication skills to translate the complex to the organization as a whole.
What You Will Do:
- Work cross functionally with business leaders across operations, marketing and member services to identify levers to drastically improve our business
- Use data science to make actionable recommendations that will drive relevant KPIs
- Understand ground truth, create training models, devise new statistical models, using machine learning techniques within the context of domain specific and domain independent data.
- Work collaboratively with the data science and product management teams to evolve current and build new quantitative product features.
Who You Are:
- Experience analyzing a subscription-based business, making actionable recommendations to drive relevant KPIs
- Experience conceiving of new metrics based on synthesis of new and existing data is highly preferred.
- You have a strong desire to work in a highly collaborative, team oriented, intellectually curious environment.
- Comfortable scoping and structuring your work in the face of a variety of different problems types such as deterministic problems, amorphous, ambiguous, and otherwise heuristic ones as well.
- Have at least an M.S. (preferred) or Bachelors (required) in Computer Science, Operations Research, Computational Economics, Statistics, Applied Mathematics, Data Science, or related major.
- Demonstrable hands-on experience in Machine learning (Bayesian Analysis, Decision Trees, Random Forests, Boosted Trees, Support Vector Machines, Neural Networks, etc.) and Advanced mathematics to create product features.
- 5+ years experience leveraging the Python Data Science stack (scikit-learn, Numpy, Pandas, etc.) to drive prototyping of large data sets. Experience with auto model building tools such as DataRobot, AutoML, et al. is highly desired.
- Experience modeling risk related problems, particularly those with class imbalances is highly preferred.
- Skilled in cleaning, transforming and otherwise statistically describing data for the purpose of feature engineering. Experience with Feature Tools or similar is highly preferred.
- Proficient in leveraging a variety of visualization packages and applications such as Tableau, Looker, matplotlib, Python dash, plotly, et al. to expose meaningful insights in data.
- Experience working with data warehouses and/or relational databases and SQL in a real-world context.