StreetLight Data Remote Full-time

StreetLight pioneered the use of Big Data analytics to shed light on how people, goods, and services move, empowering smarter, data-driven transportation decisions. The company applies proprietary machine-learning algorithms and data processing resources to measure travel patterns of vehicles, bicycles and pedestrians that enable complex transportation problem solving using analytics available on SaaS platform, StreetLight InSight®. Acquired by Jacobs as a subsidiary in February 2022, StreetLight continues to provide innovative digital solutions to help communities reduce congestion, improve safe and equitable transportation, and maximize the positive impact of infrastructure investment.
StreetLight Data is seeking a creative, versatile, and motivated Data Scientist to be part of our growing team. This team member will be responsible for characterization and quality control for the metrics and data pipeline supporting StreetLight Data’s suite of products. They will help ensure StreetLight’s metrics appropriately meet real-world expectations and customer scenarios, and contribute to the development of the analytics and data pipeline as needed. This position reports to the Data Science Manager, Validations team.
Location: Remote or Hybrid (if close enough to an office) in the United States
       Characterize, validate and monitor the quality of StreetLight’s metrics, algorithms, and data artifacts.
       Assist with the design and implementation of algorithms to infer key transportation patterns from various data sources.
       Perform Data QA on incoming data feeds and investigate data anomalies.
       Aggregate and process real-world data for modeling and validation efforts.
       Produce written documentation and technical reports for internal stakeholders and customers.
       Create visualizations and dashboards to help tell stories with data.
       Define and implement customized and/or cutting-edge solutions for customers.
       BS/MS in Mathematics, Computer Science or an Engineering discipline from a top university, or a PhD focused on quantitative research.
       2+ years of experience in data science and/or statistics, using tools such as R or Python.
       2+ years of experience in SQL and relational databases (PostgreSQL or BigQuery preferred), and good understanding of relational concepts.
       Strong understanding of techniques in data science (machine learning algorithms, regression analysis, etc.)
       Strong analytical skills, experience using data to solve problems, inform decision making, and tell stories.
       Highly organized, detail-oriented, and methodical in reporting and documenting work.
       Very strong communication skills – written, visual (presentations) and verbal.
       Technical writing skills. Experience synthesizing complex technical concepts for less technical audiences.
       Quick learner, and a strong team player.
       Eagerness to problem solve and desire to take initiative in defining requirements for ambiguous projects.  
Preferred Skills:
       Geo-spatial skills are a plus.
       Knowledge of transportation data / industry is a plus.
Pay Transparency Verbiage
Jacobs’ health and welfare benefits are designed to invest in you and in the things you care about. Your health. Your well-being. Your security. Your future. Eligible employees and their dependents may elect medical, dental, vision, and basic life insurance. Employees are able to enroll in our company’s 401k plan, and, if eligible, a deferred compensation plan and Executive Deferral Plan. Employees will also receive 17 days of vacation per year, seven paid holidays, plus floating holidays and caregiver leave. Hired applicants will be able to purchase company stock and have the opportunity to receive a performance discretionary bonus.
The base salary range for this position is $110,000 to $130,000 USD. This range reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
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