Overview
On Site
Depends on Experience
Full Time
Skills
Python
Google Cloud Platform
Machine Learning (ML)
Forecasting
Econometrics
Data Visualization
Microsoft Power BI
Tableau
NumPy
Pandas
Data Modeling
Data Analysis
Data Science
Job Details
Miracle Software Systems, seeking a Data Scientist / Analyst to join our Business and Sales Planning Analytics (BSPA) Used Vehicle Valuations team. This role involves analyzing and modeling used vehicle residual values, auction prices, and market drivers to support strategic business decisions across the U.S. and Canadian used vehicle markets.
The ideal candidate will have strong analytical skills, hands-on experience in data modeling, econometrics, and Python programming, and familiarity with Google Cloud Platform (Google Cloud Platform) for analytics and forecasting applications.
Key Responsibilities:
- Develop and maintain forecasting and econometric models to quantify relationships between auction prices and key residual value drivers.
- Deliver residual value forecasts to support key business and sales planning processes.
- Analyze and explain residual value gaps between brands and vehicle segments.
- Design and maintain data visualizations and analytics dashboards for management and stakeholders.
- Apply advanced analytical tools and integrate new data sources to improve model accuracy.
- Perform ad hoc descriptive and inferential analyses for leadership and business customers.
- Interpret and communicate analytical results to drive actionable insights.
Skills Required:
- Forecasting and Econometric Modeling
- Data Modeling and Statistical Analysis
- Python Programming (pandas, NumPy, scikit-learn, etc.)
- Google Cloud Platform (Google Cloud Platform) BigQuery, Cloud Storage, Vertex AI (preferred)
- Data Visualization Tableau, Power BI, or Looker
- Strong analytical thinking, problem-solving, and presentation skills
Education:
Required: Master s Degree in Data Science, Statistics, Economics, or related field
Experience:
Required: 1+ year of experience in data analytics, forecasting, or econometric modeling
Preferred: Automotive or financial data analysis background
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