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Forward Deployed AI-Enabled Analyst

Hiro Talent Solution
Remote

Quick Apply

Job Details

Full-time
$30 - $50 an hour

Qualifications

Cloud analytics services
Teamwork
Requirements specification
Requirements design
Cloud data warehouses
Managed care
Reporting and dashboarding tools
Schema design
Snowflake
SQL
Requirements management
Query management
Clinical data analysis
Project stakeholder communication
Design (software development lifecycle)
Entity-relationship diagrams
Data analytics technologies
Stakeholder management

Full Job Description

Core Responsibilities

Partner with product leadership and embedded client stakeholders to shape the analytics product roadmap for each engagement.
Co-develop the value narrative for analytics products targeted at payers, providers, adjusters, and internal leadership audiences.
Identify the high-impact clinical and operational metrics that anchor each product, including outcomes benchmarking, utilization trends, authorization efficiency, denial root cause, referral leakage, and network performance.
Translate ambiguous business and clinical questions into product hypotheses, measurable KPIs, and prioritized backlog items.
Conduct discovery with client and internal stakeholders to surface data gaps, unmet reporting needs, and emerging insight opportunities.
Prioritize product initiatives using a structured framework aligned to platform roadmap and the client's strategic objectives.

Requirements Translation and Technical Specification

Partner with product leadership to refine business requirements gathered from client engagements into actionable technical artifacts.
Translate high-level requirements and metrics from PRDs into detailed technical specifications that engineering can build against on first review.
Research and interpret requirements from regulatory bodies, including CMS, AHRQ, NCQA, and specialty registries, and embed them accurately into product builds.
Document technical requirements with the precision that engineering teams need to estimate, build, test, and ship without ambiguity.
Maintain requirements traceability from client problem statement through PRD, spec, build, and validation.

Data Modeling and Engineering Collaboration

Produce data product specifications that data engineering can build directly against, including entity definitions, grain, lineage, and business rules.
Collaborate with data engineering to validate model design, identify source system mappings, and define data quality requirements.
Define semantic layer requirements, including metric definitions, hierarchies, and filters, for downstream BI tools and AI agents.
Maintain a living data model catalog and analytics product dictionary as the reference for product, engineering, and client teams.

Data Assessment, Validation, and Quality Assurance

Conduct thorough analyses of client data environments to assess data quality, completeness, and usability before and during product implementation.
Verify availability and accessibility of required data elements across client source systems.
Identify data gaps, inconsistencies, or quality issues that may impact implementation, and recommend remediation paths.
Review and audit SQL logic developed by engineering teams to confirm alignment with product requirements and expected clinical or financial outcomes.
Serve as the quality checkpoint between product specifications and technical delivery, partnering with engineering to troubleshoot discrepancies and optimize solutions.

AI Enablement and Workflow Integration

Use AI tools throughout the discovery, specification, validation, and documentation lifecycle to accelerate work and improve accuracy.
Support the evaluation and integration of AI agent capabilities, including data model generation, trend intelligence, and natural language analytics, into client workflows.
Develop the prompts, evaluation criteria, and human-in-the-loop checkpoints that make AI-driven analytics trustworthy for clinical and financial decision making.
Identify opportunities to replace manual reporting workflows with AI-augmented alternatives and quantify the impact.

Documentation and Stakeholder Communication

Create clear, durable documentation that bridges business intent and technical implementation.
Communicate technical findings and data insights to both technical and non-technical audiences, from data engineers to clinical executives.
Represent credibly in client-facing forums, including working sessions, steering committees, and demos.

Required Qualifications

5+ years in analytics, product management, analytics consulting, or clinical informatics, with a meaningful portion in a healthcare context.
Direct experience designing data models, including dimensional modeling, ERDs, and semantic layer definitions, in a healthcare or managed care environment.
Strong SQL proficiency with demonstrated ability to write, read, and audit complex queries in modern cloud data warehouses such as Snowflake, BigQuery, or Databricks.
Proven ability to write product and data requirements that engineers can act on, not just business narratives.
Strong command of healthcare data constructs, including claims, authorizations, clinical episodes, utilization, denials, referrals, and outcomes.
Experience working across payer, provider, or health plan stakeholder environments, with the maturity to navigate competing priorities.
Excellent written and verbal communication, with the ability to translate fluidly between business and technical languages.

Pay: $30.00 - $50.00 per hour

Work Location: Remote

Quick Apply

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