paid / Indianapolis, IN or Charlotte, NC / full-time
Data Scientist Associate
At CLA we create inspired careers .
We recognize that not everyone wants to grow their career in the same way. That’s why CLA exists to create opportunities . We promise to know you and help you.
CLA, one of the nation’s largest public accounting and professional services firm is currently seeking a Data Scientist Associate to join our growing Digital Transformation team in our Indianapolis, IN or Charlotte, NC office.
The Data Scientist Associate thrives when constructing complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using software development best practices in R, Python, or other scripting languages. They are comfortable working with APIs, web scraping, and SQL/no-SQL databases. It is not uncommon for our Data Scientists to automate business workflows while integrating stochastic/numeric algorithms in the process. Creating and modifying predictive algorithms to uncover and answer business questions makes us tick. Our products are usually delivered as a scheduled deployment, markdown report, dashboard, shiny application, or API.
As a Data Scientist Associate, you will:
- Participate in the collection, analysis, and automated collection of data using a variety of data tools.
- Together with the Data Analytics team, support the building and implementing of models, algorithms, and simulations supporting solutions for external clients and internal projects.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Working under the guidance of a variety of Data Analytics team members, gain exposure to developing custom data models and algorithms to apply to data sets.
- Gain experience with predictive and inferential analytics, machine learning, and artificial intelligence techniques. Use existing processes and tools to monitor and
Your experience includes:
- Experience: No experience required.
- Education: Bachelor’s degree in a field of Statistics, Computer Science, Economics, Analytics, or Data Science (e.g., Informatics, Data Science, Health Data Science) required.