Data Analyst Associate; Hybrid

Position: Data Analyst Associate (Hybrid)
Location: Indianapolis

CLA is a top 10 national professional services firm where
** our purpose is to
* create opportunities
*** every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a  that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.
** Our Perks:
*** Flexible PTO (designed to offer flexible time away for you!)
* Up to 12 weeks paid parental leave
* Paid Volunteer Time Off
* Mental health coverage
* Quarterly Wellness stipend
* Fertility benefits
* Complete list of benefits

CLA is currently seeking an Data Scientist - Associate to join our growing internal IT team.
** How you’ll
* create opportunities
* in this Data Scientist - Associate role:
** This role constructs complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using software development best practices in Python, R, or other scripting languages. The role includes working within modern data platforms, such as Databricks, to develop and optimize scalable data pipelines and machine learning models, automating business workflows and answering business questions to improve CLA by integrating ML or AI algorithms into our decision-making processes, and working with and building AI/ML models, including utilizing and/or tuning Large Language Models (LLMS).
** Essential Job Functions*
* • Expand Knowledge/Exposure:
Develop service specific knowledge through greater exposure to peers, internal experts, clients, regular self-study, and formal training opportunities. Gain exposure to a variety of program/project situations to develop business and organizational/planning skills. Retain knowledge gained and performance feedback provided to transfer into future work. Approach all problems and projects with a high level of professionalism, objectivity and an open mind to new ideas and solutions.
• Data Analysis & AI Solutions:
Collaborate with internal teams to collect, analyze, and automate data processing. Leverage AI models, including LLMs, for developing intelligent solutions that enhance data-driven decision-making processes for both internal projects and external clients. Leverage machine learning methodologies, including non-linear, linear, and forecasting methods to help build solutions aimed at better understanding the business of CLA, making CLA more efficient, and planning our future.
• Data Development:
Working under the guidance of a variety of Data Science 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 analyze solution performance and accuracy and communicate findings to team members and end users.
• AI-Driven Workflows:
Contribute to automating business workflows by incorporating LLMs and other AI models to streamline processes and improve efficiency. Integrate AI-driven solutions within existing systems to provide advanced predictive capabilities and actionable insights.
** Key Responsibilities*
* • Collect, clean, and analyze data using Python.
• Transform and prepare data for analysis using Python libraries such as pandas and numpy.
• Support model development and testing under the guidance of senior data scientists.
• Develop visualizations using matplotlib, seaborn, or plotly to communicate findings.
• Contribute to AI and machine learning projects through data preparation and validation tasks.
• Work in collaborative environments using Git, Databricks, and other modern data tools.
• Document analytical processes clearly and maintain accurate records of analysis and results.
• Engage in ongoing learning to build deeper expertise in data science tools and methods.
** Technical Environment and Tools*
* • Python (pandas, numpy, matplotlib, seaborn, scikit-learn)
• SQL for data…