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- Master at analyzing big data and operating in multiple data environments
- Ability to proactively identify areas of opportunity and creatively develop solutions in a timely manner
- Able to effectively work across teams and clearly articulate results to end users
- Masters degree (mathematics, statistics, engineering, computer science) or Bachelors degree with 2 or more years of work experience
- Experience developing models, algorithms and code independently using Python, Pyspark, SQL. AWS
- History of successful development and deployment in production environments
- Experience with Databricks, Python and Tableau preferred
- This role is focused on vehicle valuations using data to understand value variations due to geography, seasonality and condition. No previous experience is needed in vehicle valuations.
- Curate data from many sources, including internal databases and external APIs, and aggregate to a format appropriate for building descriptive reports or predictive models
- Solve complex analytical problems using quantitative approaches using unique blend of technical, business mathematical, analytical and data skills
- Use deep understanding of statistical and predictive modeling concepts, machine learning approaches, clustering and classification techniques, and recommendation and optimization algorithms
- Analyze large, complex multi-dimensional data sets with variety of tools
- Partner with business stakeholders to prepare and maintain reports/dashboards that will be used to derive insights into past/present business performance Responsibilities
- Develop, maintain, and continuously improve fleet procurement, in-fleeting, and vehicle value models to inform procurement negotiations and drive improved profitability
- Develop, maintain, and continuously improve modeling and other models to support the optimization of fleet procurement spend
- Build & deploy predictive models to increase customer retention & profitability (i.e. digital recommendation engines)
- Build & deploy tools to enable proactive customer recovery
- Support the development of integrations with new data sources and evolution of fleet and industry data lake using data from multiple sources, including internal databases and external APIs
- Partner with business stakeholders to prepare and maintain reports/dashboards that will be used to derive insights into past/present business performance
- Provide input on design and testing of various forecasting methodologies as it relates to fleet purchase pricing, residuals, procurement channels and other areas as needed
- Develop forecasting models to help meet fleet demand levels
- Successful candidates will be able to demonstrate a higher proceeds from vehicle sales by identifying opportunities to:
- relocate vehicles prior to selling fleet vehicles.
- buy in one market and selling in another.
- repair vehicles prior to selling
- buy wholesale and sell retail