Data Scientist
On-siteAnn Arbor, Michigan, United States
Job Summary
Conduct data collection, cleaning, and preprocessing to prepare geospatial datasets for analysis. Develop and implement statistical models and machine learning algorithms to address business problems, including building predictive models using established frameworks. Collaborate with cross-functional teams to understand data requirements and deliver actionable insights for store openings in domestic and international markets. Document methodologies and monitor model performance to ensure reproducibility and maintain data pipelines. Extract and transform data using Python, SQL, and ArcGIS tools, while generating reports and visualizations to communicate findings to stakeholders.
Required Qualifications
- 1 to 3 years of professional experience in data science or related analytical roles
- Completion of a degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or a related discipline
- Proficient in data manipulation and exploratory data analysis with attention to data quality
- Basic understanding of machine learning concepts and ability to apply standard algorithms
- Effective communication skills for presenting technical information to non-technical audiences
- Ability to work under general supervision while managing multiple routine tasks
- Familiarity with version control and collaborative development practices
- Experience with geospatial data analysis tools, including ArcGIS (arcpy), Pandas/GeoPandas, Geospatial SQL, etc
- Python for data analysis and modeling
- SQL for data extraction and manipulation
- Experience with ArcGIS
- Data visualization tools such as Tableau, Power BI, or matplotlib/seaborn libraries
- Jupyter Notebooks or similar integrated development environments
- Version control systems such as Git
- Experience with Fast API creation (i.e. functional programming, automated testing, performance optimization techniques)
- Experience applying algorithms to large-scale data (e.g. supervised/unsupervised, optimization/solver)
- Experience with Geospatial data types
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