Towne Park is looking for a Data Scientist to support their dynamic pricing initiatives by building and refining models to predict parking demand and optimize pricing for commercial and hotel parking facilities, ultimately improving parking management efficiency.
Requirements
- Solid experience with machine learning algorithms (e.g., regression, classification, time series forecasting) and statistical techniques
- Proficiency in Python (or R) and SQL
- Strong knowledge of data manipulation, analysis, and visualization tools
- Experience with cloud computing platforms (e.g., Azure, Snowflake, AWS, GCP) and data storage solutions (e.g., SQL, NoSQL).
- Experience building Streamlit or Shiny apps
- Experience with A/B testing and experimentation
- Ability to write production-ready code
Responsibilities
- Develop ML models to forecast parking demand
- Build and optimize dynamic pricing models that adjust prices based on predicted demand and other relevant factors
- Implement machine learning algorithms and statistical models to predict demand accurately.
- Analyze historical data and market trends to identify patterns and inform pricing strategies.
- Monitor and evaluate model performance over time, making improvements as needed
- Communicate findings and insights through clear and compelling data visualizations and reports.
- Stay up to date with industry best practices in data science and machine learning.
Other
- 3+ years of professional experience in data science or a related role, with a strong emphasis on predictive modeling and optimization
- Excellent communication skills, both written and verbal, with the ability to present technical concepts to non-technical stakeholders.
- Strong problem-solving skills and the ability to work independently and collaboratively.
- Travel of up to 20% may be required.
- Bachelor’s or master’s degree in computer science, Data Science, Statistics, Economics, Engineering, or a related field
