Analytics Engineer I (Entry-Level) (3897)

Responsibilities

• Aid in designing, building, and maintaining data pipelines and ETL/ELT processes.
• Write and optimize SQL queries to extract, transform, and analyze data from multiple sources.
• Support the development of dashboards and reports using Excel and other business intelligence tools.
• Utilize Python and/or R to automate data workflows, clean datasets, and perform exploratory analysis.
• Contribute to AI/ML-driven workflows for extracting key text and structured data from documents, including NLP, LLM-based extraction, and OCR plus ML pipelines.
• Collaborate with data scientists, analysts, and business stakeholders to understand data and applied AI project needs.
• Document data models, pipeline logic, and AI/ML workflow processes.
• Contribute to data quality checks and validation processes for both traditional data and AI-generated outputs.

Requirements

• Bachelor's degree in Data Analytics, Statistics, Computer Science, Mathematics, Engineering, or a related field.
• Working knowledge of SQL for querying and manipulating data.
• Proficiency in Excel, including formulas, pivot tables, and data visualization.
• Proficiency in Python and/or R, including experience with relevant ML/AI libraries such as pandas, scikit-learn, or similar tools.
• Hands-on exposure to AI/ML concepts through coursework, projects, or internships, such as text extraction, natural language processing, or document processing.
• Strong analytical and problem-solving skills.
• Good communication skills and the ability to work in a collaborative, cross-functional environment.
• An attention to detail and a commitment to data accuracy.

Preferred Qualifications

• A Master's degree in a relevant quantitative field.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud and BI tools such as Tableau, Power BI, or Looker.
• Familiarity with version control, such as Git, and basic software engineering practices.
• Experience with LLM-based tools or APIs for document parsing, text extraction, entity recognition, or information extraction.
• Experience with OCR tools or unstructured document processing, including PDF or text parsing libraries.