Senior AI Analytics Engineer

International Oncology Network Solutions Inc

Town of Texas (WI)

Hybrid

USD 90,000 - 125,000

Full time

5 days ago

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Job summary

International Oncology Network Solutions Inc seeks an experienced Senior Analyst, Technical Business Solutions to translate business needs into analytics specs and deliver AI-enabled solutions. You will work with client services, product, engineering, and architecture to align requirements and timelines, document decisions, and enhance analysis practices across the team.

You will refine requirements, manage backlogs, and collaborate on API integrations while focusing on reliable delivery and

Qualifications

Bachelor's degree in business administration, computer science, information systems, or related field or equivalent experience.
4+ years of experience in technical business analysis, data analytics, solution design, or related field.
3+ years of experience with SQL and Python.
2+ years in DevOps.
2+ years hands-on with GenAI / LLM-based applications.
Proven experience with REST APIs (FastAPI or Flask).
Strong understanding of prompt engineering principles and practices.
Familiarity with RAG concepts in data retrieval.
Knowledge of Azure Data Factory and Databricks is a plus.
Experience with PowerBI is a plus.
Demonstrates ability to translate business needs into technical solutions across domains.
Proven ability to deliver high-quality results on complex components and improve delivery outcomes.
Ability to work independently and in a team.
Excellent written and verbal communication skills.

Responsibilities

Assess business needs and user requirements to craft actionable specs for AI and analytics solutions.
Collaborate with client services, product, engineering, and architecture to align on scope and dependencies.
Evaluate options by analyzing value, impact, feasibility, risk, and standards to recommend approaches.
Maintain documentation of requirements, workflows, and acceptance criteria.
Participate in backlog discussions, translating requirements into structured inputs.
Improve requirement methods and analysis practices to reduce rework and improve delivery.
Identify and resolve reporting defects and data discrepancies through analysis.
Develop strategies for utilizing RAG in BI and analytics.
Refine prompts to improve user-AI interactions.
Ensure seamless integration of API functionalities into existing systems.