Job Description
Staff Data Scientist, Offering and Pricing
Location
Remote, USA
Type
Full time
Department
Tech
Compensation
- $190K $210K Offers Equity
About Veho
Veho is the post-purchase experience company that unlocks the potential of everyday consumers and brands to fully participate in e-commerce. Building an entirely new end-to-end logistics infrastructure, powered by the latest technology and designed for the modern era of shopping, Veho is reinventing shipping, and all parts of the post-purchase experience as we know it. By removing the pain from delivery and returns, Veho is creating powerful opportunities for brands to engage and build deep loyalty with their customers like never before.
About The Role:
As a Staff Data Scientist, youll 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 our logistics network and user experiences. Youll partner with product managers to understand high-value business problems, build systems that inform daily operations, and work with cutting-edge technology. Youll work closely with software engineers to operationalize the models you build in the production systems that drive Veho.
Responsibilities Include:
- Helping Shape Roadmaps by integrating business context and Data Science.
- Building reliable, efficient, and scalable models for our AI/ML capabilities
- Creating robust data pipelines to feed analyses and models
- Analyze and evaluate the impact and effectiveness of models in production systems
- Driving science roadmap for pricing of gig economy work for Veho alongside cross-functional partners.
What You Bring:
- Bachelors Degree plus 8 years of experience in data science or data engineering, or Masters Degree plus 5 years in data science, Or Phd plus 3 years of experience in Data Science
- Experience using statistical modeling and machine learning techniques to solve business problems
- Experience developing both greenfield systems and building on top of existing systems.
- Experience leading end-to-end machine learning and data science projects.
- Strong SQL and Python skills.
- Experience with MLOps and model deployment pipelines
- Experience with Causal Inference / Advanced Experimentation Methodologies is nice to have, but not required.
- Experience with recommendation systems is nice to have, but not required.
- Experience with pricing methodologies is nice to have, but not required.
- Experience with logistics is nice to have, but not required.
- Experience with combinatorial optimization methods is nice to have but not required.