Full Stack Data Scientist at Veho

About Veho

Veho is a technology-driven shipping company that enables personalized next-day package delivery, extending partner brand value. Veho brand partners have seen a 20% increase in customer repurchase, 40% increase in customer lifetime value, and 8% rise in net promoter score.  

Veho gives package recipients greater insight and control, letting them know when they will receive their package, when drivers are en route, and enables real-time rescheduling, address changes, and personal delivery instructions. Veho's technology matches demand for package delivery with a network of qualified crowdsourced driver partners, ensuring every package is delivered on time and correctly.

The concept for Veho started as a school project while co-founder Itamar Zur attended Harvard Business School. Zur constantly experienced issues receiving packages - from getting the dreaded “we missed you” note, to stolen packages. He set out to fix the problem so many customers and brands face.

Today, Veho’s robust technology platform provides customers and e-commerce brands with an unparalleled shipping experience, an industry record 99.9% average on-time performance for next-day delivery and an average 4.9-star customer rating. With teammates in 30 U.S. states, Veho will be in 50 markets by the end of 2022.  

As a Full-Stack Data Scientist, you’ll be directly embedded in a team of talented software engineers to help define, build, and operate sophisticated models to answer hard questions centered around improving user experiences.  You’ll partner with product managers to understand high-value business problems, build systems that inform daily operations, and work with cutting edge technology.  You’ll work closely with software engineers to operationalize the models you build in the production systems that drive Veho.  


Responsibilities Include: 

Understanding business context and gathering requirements
Building and iterating on models to meet requirements using Python or some other language
Building and iterating on data pipelines to feed analysis and productized models
Integrating models into production systems using MLOps best practices
Ensuring data quality and data integrity through best practices in data integration
Analyzing impact and effectiveness of models in production systems



What You Bring:

Bachelor’s Degree plus 5 years of experience in data science or data engineering, or Master’s Degree plus 3 years in data science or data engineering
Basic understanding of statistical techniques like k-means clustering, regression, or decision trees
At least 3 years of experience with open source languages and tooling used for large-scale data analytics like Python, numpy, and/or distributed data processing systems like spark
At least 1 year of experience with analytical relational databases like Redshift, BigQuery, or Snowflake
At least 1 year of experience working with AWS and its data engineering and data science tools
Experience with vehicle routing problems or logistics is nice to have, but not required



#LI-Remote

Veho is a growth company that looks for team members to grow with it. Veho offers a generous ownership package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Veho employee shares one galvanizing mission:  to revolutionize the world of package delivery by creating exceptional experiences for customers and drivers.  We are deeply value-driven (Ownership, Candor, Team Success, Human) and care tremendously about investing in people.  We are committed to creating a diverse team and an environment that provides everyone with the opportunity to do the work of their lifetime. Veho is unable to provide sponsorship at this time.  Applicants must be able to understand and effectively communicate orally and in writing with all parties regarding work matters, which are generally conducted in English.  Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.