Data Scientist Sr

COUNTRY Financial•Bloomington, IL

About The Position

COUNTRY Financial is seeking a Senior Data Scientist to join our Information Technology department. This position leads the design, development, and deployment of data-driven solutions to drive innovation and cost reduction for our business and technology partners. The ideal candidate is comfortable working with structured data, writing Spark jobs, and building models to support reporting or automation needs.

Requirements

Typically requires 7+ years of relevant experience or a combination of related experience, education and training.
Proven experience as a Machine Learning Engineer or similar role
Proficiency in managing and maintaining ML/AI development and deployment environments
Experience with AI Engineering and Architecture
Understanding and experience with Cloud-based Infrastructure
Proficiency in Python and SQL
Recent experience working with vendors on build and delivery of data models/AI solutions
Experience with PySpark, Hive, and the Cloudera platform
Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
Familiarity with machine learning workflows using scikit-learn or similar libraries
Strong attention to detail and ability to follow established IT processes
Strong knowledge of GitLab and experience in maintaining CI/CD pipelines
Proficiency in data engineering and ETL processes
Experience with cloud platforms such as Azure, AWS, or Google Cloud
Knowledge of DevOps practices and tools
Understanding of version control and CI/CD processes (ex: GitLab CI)
Familiarity with Jupyter Notebooks and dashboarding tools (ex: Tableau)
Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch)
Excellent problem-solving skills and attention to detail
Strong communication and collaboration skills
Prior experience working in insurance or regulated environments

Responsibilities

Build and maintain robust Machine Learning (ML) and Artificial Intelligence (AI) models and deployment environments
Drive activities with a special focus on model engineering and deployment of code to production workflows
Work with IT and business stakeholders to understand requirements and translate them into technical solutions
Develop data pipelines using PySpark and Hive within the Cloudera ecosystem
Expand the use of AI, Large Language Models (LLM), and Retrieval Augmented Generation (RAG) capabilities
Build and validate machine learning models for classification, regression, or clustering tasks.
Write queries and perform analysis on large datasets using Hive and SQL
Contribute to documentation, testing, and model handoff to ensure stability and maintainability
Maintain and optimize GitLab templates for efficient workflow automation
Ensure the scalability and reliability of ML/AI infrastructure
Monitor and troubleshoot issues related to ML/AI pipelines and deployments
Stay updated with the latest advancements in machine learning and AI technologies
Engages with business to understand business problems to be solved. Helps business frame problems in a way that can be addressed with analytics.
Performs data mining and transforms raw data into actionable business information.
Develops and implements data-driven business solutions using advanced statistical methods and machine learning techniques.
Uses a flexible, analytical approach to design, develop and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. Validates model performance using the appropriate standards/error metrics. Manages version control and documentation of data.
Develops and produces supervised and unsupervised machine learning, forecasting and optimization.