HopSkipDrive is hiring a
Senior Data Scientist

Summary

Join HopSkipDrive as a Data Scientist and leverage organizational data to generate meaningful insights that improve user experiences and business efficiency. The ideal candidate will have experience building and deploying production quality predictive and prescriptive models, strong data acquisition skills, and the ability to communicate results to stakeholders.

Requirements

• 6+ years of hands-on experience building and deploying production quality predictive and/or prescriptive models
• Strong data acquisition skills using SQL in modern technical stacks (PostGres, AWS, Snowflake)
• 6+ years of post-graduate experience working with open source data science toolkits including Python (numpy, pandas, scikit, PySpark) or R (Tidyverse/Tidymodels). Strong preference for candidates who can capably translate between Python and R
• 2+ years experience in deploying models to production environments through APIs, or batch processes
• 3+ years experience in at least TWO of the following DS methods
• Supervised and Unsupervised ML (regression, classification, etc.)
• Econometric modeling (e.g. time-to-event/survival analysis)
• Reinforcement learning (e.g multiarm bandits for price or intervention optimization)
• Operations research (e.g. combinatorial optimization/ traveling salesman, linear programming)
• Demonstrated experience with reproducible data science environments including creation of virtual environments, library management, and version control using Git/Github
• Demonstrated experience writing up results using literate programming workflows (Quarto preferred)

Responsibilities

• Combine DS strategies, programming expertise, and theoretical understanding of techniques to deliver advanced ML solutions for problem solving across the enterprise
• Scope, explore, specify, test, and deploy, and observe accurate and stable models into production environments
• Utilize modern, open-source data scientific workflows (SQL, R/Python, Github) to create highly accurate or explainable predictive/prescriptive models
• Own models in production and re-train when necessary
• Demonstrate a product mindset to deliver portable components that can be deployed into existing products OR converted into stand-alone data products
• Partner closely with BI, Engineering, Product Management, DevOps, and business stakeholders to create business-aligned, stable workflows
• Communicate results and model specifications to appropriate stakeholders
• Mentor, train, and assist aspiring data science professionals

Benefits

• Competitive market comp
• Flexible vacation
• FSA
• Medical, dental and vision
• 401(k)
• Equity stock options