Data Scientist

American Traffic Solutions   •  

Mesa, AZ

Industry: Transportation


5 - 7 years

Posted 173 days ago

This job is no longer available.

Who we are...

Verra Mobility is a global leader in smart mobility. We develop technology-enabled solutions that help the world move safely and easily. We are fostering the development of safe cities, working with police departments and municipalities to install over 4,000 red-light, speed, and school bus stop arm safety cameras across North America. We are also creating smart roadways, serving the world's largest commercial fleets and rental car companies to manage tolling transactions and violations for over 8.5 million vehicles. And we are a leading provider of connected systems, processing nearly 165 million transactions each year across 50+ individual tolling authorities.

Position Overview

The Data Scientist is responsible for applying advanced analytics to provide accurate, relevant, and actionable insights that enable Verra Mobility to make smarter decisions and deliver even better products and services to our customers. This role works closely with data scientists/analysts, engineers, product/project management and collaborates with other cross-functional teams to turn data into insights and turn insights into actions to help the business improve efficiencies and drive new opportunities.

This position requires strong research and analytics skills, and ability to understand broad problem/decision context, frame the problem, and perform necessary research and analysis to draw relevant and insightful conclusions from often incomplete information.

About You:

  • You have a trained eye to find new opportunities by delving into process. These opportunities can be in automation or in new ways to leverage the company’s data.
  • You are inquisitive and curious with a desire to understand customer behavior. You are able to uncover insights in customer data through disciplined, scientific practices ranging from developing, designing, and testing hypotheses to implementation of solutions.
  • You love to collaborate with industry experts to stress test and understand the limitations of your models.
  • You are capable of prioritizing business needs and you can independently design solutions.
  • You are comfortable with explaining technical problems in business.

Essential Responsibilities

The responsibilities of this position include, but are not limited to, the following:

  • Research and develop machine learning, data mining and other analytics algorithms/applications.
  • Aggregate, analyze data and information and create algorithms/models/applications to produce relevant and actionable insights.
  • Synthesize data, information, and knowledge to form conclusions and recommendations.
  • Communicate insights and findings to stakeholders through effective presentations, reports, dashboards, scorecards, and other visualization tools.
  • Perform ad-hoc analysis and present results in a clear and concise manner.
  • Research, gather, structure, and validate data and information from various sources, extend company’s data with third party sources when needed.
  • Work closely with data architects/engineers to structure data for efficient, scalable, and reliable analysis.
  • Work closely with software engineering teams to implement algorithms/models/applications.


  • Master’s Degree or Ph.D. in Computer Science, Applied Mathematics, Statistics, or in another highly quantitative field and at least 4+ years of professional work experience.
  • Advanced degree in a quantitative field.
  • Experience in machine-learning techniques and their mathematical foundations; experience in NLP (Natural Language Processing).
  • Experience in formulating and solving business problems with actionable and reproducible outcomes with measurable impact.
  • Significant experience developing analytics algorithms, models and applications using Python, R, or Scala; C++ is a plus.
  • Experience with common statistical analysis and computing tools.
  • Experience in Design of Experiments and split testing methods.
  • Solid understanding of Statistics.
  • Experience in time-series analysis and forecasting.
  • Knowledge of statistical analysis and machine learning algorithms and techniques, such as k-NN, Naive Bayes, SVM, Random Forests, neural networks, etc.
  • Experience writing non-trivial SQL scripts.
  • Strong critical thinking and problem-solving skills.
  • Strong verbal and written communication skills.
  • Strong organizational skills with the ability to manage multiple assignments and work autonomously in a fast-paced environment.
  • Detail oriented and have a hands-on, "get it done" attitude.