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CLEAR is a cutting edge biometric tech company bringing future of travel to passengers.
 
Engineering, Full Time    New York City, United States    Posted: Thursday, March 07, 2019
 
   
 
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JOB DETAILS
 

CLEAR transforms what is uniquely you your fingerprints, your face, your eyes into a secure, biometric key to frictionless experiences. We are creating a world where travel is effortless, where accessing your office building is as simple as walking in, & where shopping is as easy as walking in & out of a storewithout ever once showing an ID or credit card. CLEAR currently powers secure, frictionless customer experiences in nearly 40 U.S. airports & venues. With over 3 million members so far, CLEAR is the identity platform of the future, today.

Through cutting edge biometrics & advanced Homeland Security certified data algorithms, CLEAR products guarantee identity & protect our members, while speeding them through security.Were seeking an innovative, intellectually curious & results-oriented Data Scientist to support, enhance & expand CLEARs current & projected security & identity algorithms. As a critical member of our research & development team, you will have a prominent voice in the future of our company. Youre a deep thinker who enjoys solving critical problems, & can own a solution from end to end.

You are technically proficient & have the ability to access & wrangle large amounts of structured & unstructured data, a great business sense, the desire to influence strategic decisions with data-driven analysis. You are passionate about applying data science towards solving business problems, particularly within the context of quantitative product features. You think deep, you happily prove your assumptions & you work fast. Lastly, you have strong written & verbal communication skills.


What You Will Do:

  • Define data requirements & gather & validate information, applying judgment & statistical tests. Ability to prototype code for the newly researched methods to support the integration of new algorithms. Writing production ready code is a plus.
  • Understand ground truth, create training models, devise new statistical models, using machine learning techniques within the context of domain specific & domain independent data.
  • Work collaboratively with the data science & product management teams to evolve current & build new quantitative product features.
  • Work collaboratively with engineering to integrate new product features into production.

Who You Are:

  • You have a strong desire to work in a highly collaborative, team oriented, intellectually curious environment.
  • Comfortable scoping & structuring your work in the face of a variety of different problems types such as deterministic problems, amorphous, ambiguous, & 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.) & 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 managing your code in a modern day version control system, eg git.
  • Experience modeling risk related problems, particularly those with class imbalances is highly preferred.
  • Experience conceiving of new metrics based on synthesis of new & existing data is highly preferred.
  • Skilled in cleaning, transforming & 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 & 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 & SQL in a real-world context. Experience with Snowflake is highly preferred.
 
 
 
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