Data Analyst, AI & ML (Chicago-based)

***Candidates must be authorized to work in the United States***

If you're naturally curious, comfortable working with large datasets, excited by the rapid advancement of AI technologies, and eager to apply those tools to real-world business problems, this role offers exceptional exposure, meaningful responsibility, and long-term growth opportunities within a fast-moving SaaS environment!

• Competitive Compensation: the hourly pay rate is $25.
  
• Contract Duration: This role begins with an initial 3-month evaluation period and is intended to transition into a longer-term opportunity for the right individual.
  
• Robust Benefits Package: a well-rounded package designed to support your health, financial security, flexibility, and long-term growth, including major medical, dental, and vision coverage, company-sponsored life insurance, a 401(k) with company matching, commuter benefits, generous PTO, paid sick time, and company holidays.
  
• Perks That Support You: a continuous learning stipend, paid parental leave with extended work-from-home flexibility for new mothers, company-wide celebrations, and an annual global summit that brings teams together.
  
• Snack & Beverage Fuel: a fully stocked kitchen with snacks, drinks, and grab-and-go options to keep energy high and focus sharp throughout the day.
  
• In-Office, Hybrid Schedule by Design: our team comes together in our Downtown Chicago office Tuesday through Thursday for high-impact collaboration, with Mondays and Fridays reserved for focused remote work.
  

• Bachelor's degree in Data Science, Analytics, Computer Science, Information Systems, Business Analytics, Marketing Analytics, or a related field.
  
• 1+ years of professional, academic, internship, research, or project-based experience involving data analysis, business intelligence, analytics, AI tools, or related disciplines.
  
• Demonstrated experience utilizing AI tools such as Claude, ChatGPT, Gemini, Copilot, or similar platforms to improve productivity, research, analysis, or decision-making.
  
• Basic familiarity with data analysis concepts, data quality principles, and working with structured datasets.
  
• Exposure to Artificial Intelligence, Machine Learning, Natural Language Processing (NLP), Entity Recognition, or related AI concepts.
  
• Ability to leverage AI tools to solve business problems, perform research, analyze information, and generate actionable insights.
  
• Strong analytical thinking and problem-solving skills with the ability to investigate questions and identify practical solutions.
  
• Excellent curiosity, adaptability, and willingness to learn emerging technologies and analytical methodologies.
  
• Strong written and verbal communication skills with the ability to clearly present findings and recommendations.
  
• Comfortable working in a collaborative environment where priorities, technologies, and business needs may evolve rapidly.
  

• Leverage AI tools such as Claude, ChatGPT, and other emerging technologies to accelerate data analysis, research, problem-solving, and workflow efficiency.
  
• Analyze large-scale datasets to identify trends, anomalies, opportunities, and actionable business insights.
  
• Support data enrichment, validation, cleansing, and quality improvement initiatives across millions of search and marketing intelligence records.\
  
• Assist with identifying relationships between entities, search behaviors, topics, brands, and content using AI-assisted analytical techniques.
  
• Partner with Product, Data Science, and Engineering teams to evaluate new datasets, data sources, and AI-driven opportunities.
  
• Utilize AI-assisted workflows to investigate business questions, generate insights, and improve operational processes.
  
• Develop Proofs of Concept (PoCs) that demonstrate how emerging AI technologies can improve data quality, analysis, and product capabilities.
  
• Validate data accuracy and integrity while helping maintain the quality standards required for enterprise-scale applications.
  
• Document findings, recommendations, methodologies, and process improvements in a clear and organized manner.
  
• Continuously evaluate new AI tools, workflows, and technologies that can improve team productivity and analytical capabilities.
  
• Support a fast-moving environment where experimentation, adaptability, curiosity, and continuous learning are highly valued.
  

• Experience with Python, SQL, R, Tableau, Power BI, Looker, or similar analytical tools.
  
• Experience working with large datasets, search data, marketing data, SaaS platforms, or AI-driven technologies.
  
• Exposure to Natural Language Processing (NLP), Entity Recognition, Machine Learning, Knowledge Graphs, or Information Retrieval concepts.
  
• Experience using AI-assisted workflows to automate repetitive tasks, improve analysis, or accelerate decision-making.