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Data Scientist Financial Intern
3 months ago
Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.
Summary:
The Data Scientist intern will report to the Senior Financial Analyst and support the Financed and Accounting teams with insights gained from analyzing company data. The ideal candidate must be proficient at using large data sets to find opportunities for process optimization. The candidate must also be adept in turning optimized results into dashboards leveraging PowerBI, Qlik, Tableau, or other similar data applications. The candidate must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams as well as working independently. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Responsibilities:
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases to drive optimization and improvement of product development and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize revenue generation and other business outcomes.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
Qualifications:
- Strong problem-solving skills with an emphasis on optimization.
- Ability to work independently; must be self-starter.
- Some experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.