Data Scientist

AArete•Chicago, IL

2d•$90,000 - $120,000•Hybrid

About The Position

AArete is seeking a Data Scientist to support client teams by providing insights derived from advanced analytics techniques. The ideal candidate will have a proven ability to drive business results through data-driven insights and be comfortable collaborating with diverse stakeholders and functional teams. This role will be instrumental in formulating data-driven solutions aligned with business requirements. In the evolving landscape of AI, this position will focus on designing, evaluating, and operationalizing advanced Generative AI and Agentic AI solutions to enhance analytical workflows, expedite client delivery, and translate complex data into actionable business strategies.

Requirements

3-5 years of work experience with a bachelor’s degree in quantitative field such as Computer Science, Statistics, Economics, Math, Engineering, advanced degree preferred
Previous experience working with relational databases and developing advanced SQL queries is a must
Hands-on Agentic AI experience, including building or evaluating AI agents, multi-step AI workflows, tool/function calling, retrieval-augmented generation, or workflow orchestration frameworks
Advanced Generative AI experience, including prompt engineering, LLM application design, model evaluation, responsible AI practices, and practical implementation of AI-enabled solutions
Strong Python experience for data science, machine learning, model experimentation, automation, API integration, and production-quality analytical workflows
Solid AI/ML background with practical experience across supervised learning, unsupervised learning, model validation, feature engineering, statistical analysis, and business-focused experimentation
Demonstrated ability to learn and adapt quickly in fast-changing AI environments, with passion for AI, curiosity, and a continuous learning mindset
Strong problem-solving skills with the ability to structure ambiguous business questions, test hypotheses, and deliver practical analytical recommendations
Experience leveraging AI assistive tools such as Claude Code, GitHub Copilot, or similar tools to accelerate coding, analytics, documentation, testing, and solution development
Experience working with business intelligence platforms: Tableau, Power BI, etc.
Must be legally authorized to work in the United States without the need for employer sponsorship

Nice To Haves

Based in Chicago, IL, and flexible to work from our Chicago office as needed
Healthcare industry experience, especially with payer, provider, clinical, claims, revenue cycle, population health, or healthcare operations data
AWS cloud experience, including familiarity with services such as Amazon SageMaker, Amazon Bedrock, Lambda, S3, or related cloud-native AI/ML services
Snowflake experience, including data modeling, SQL optimization, secure data sharing, or analytics engineering in cloud data warehouse environments
Consulting background with experience working directly with clients, managing ambiguity, and delivering executive-ready recommendations
AWS AI or machine learning certifications, such as AWS Certified Machine Learning Engineer, AWS Certified Machine Learning Specialty, AWS Certified AI Practitioner, or related AWS credentials

Responsibilities

Mine and analyze data to drive optimization and improvement of business strategies
Develop custom AI/ML models and algorithms to apply to data sets
Develop processes and tools to create and monitor data models while maintaining accuracy and other associated metrics necessary for the business objective
Design, prototype, and evaluate Agentic AI workflows, including tool-using agents, retrieval-augmented generation, orchestration patterns, and human-in-the-loop controls
Apply advanced Generative AI techniques, including prompt engineering, model evaluation, grounding, safety guardrails, and responsible AI practices, to solve client business problems
Leverage AI assistive engineering tools such as Claude Code, GitHub Copilot, or similar platforms to improve development velocity, code quality, documentation, and experimentation
Partner with business and technical stakeholders to rapidly learn new domains, frame ambiguous problems, and translate AI/ML opportunities into measurable client outcomes
Other duties as assigned