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Inabia Software & Consulting Inc. logo

Lead Healthcare Analytics Consultant

Inabia Software & Consulting Inc.
Posted 1 weeks ago
🇺🇸United States🏠Remote📁Data & Analytics
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Overview Inabia is seeking a remote Lead Healthcare Analytics Consultant for a 6-month contract engagement to serve as a technical lead driving data and analytics excellence across key stakeholder relationships. This role moves well beyond standard reporting, requiring an AI-first mentality and the ability to translate complex healthcare claims data into clear, actionable narratives that influence business decisions. The ideal candidate is a self-starter who thrives in high-pressure environments, capable of owning high-priority projects with tight turnaround times while leading by example. Responsibilities Lead the end-to-end analytics lifecycle for leadership and key stakeholders, ensuring high-impact reporting is delivered on schedule and strategically aligned with clinical and financial objectives. Serve as the primary analytics lead for top-tier client requests, designing solutions that address complex healthcare business challenges and presenting insights directly to key partners. Establish and uphold data integrity standards by leading peer code reviews and providing expert guidance on SQL optimization, complex logic validation, and adherence to data governance and compliance requirements. Oversee the reporting roadmap and project lifecycle via Jira and Confluence, ensuring transparent communication of project statuses, maintaining technical documentation, and proactively identifying risks to delivery timelines. Act as the voice of the data for key stakeholders, translating dense healthcare findings into compelling narratives and high-level presentations that bridge technical complexity with business-critical decision-making. Lead high-priority routine and ad-hoc analyses, including internal and external audits, and deliver insights within accelerated timeframes when required. Identify bottlenecks in the data lifecycle and partner with Data Engineering and Data Architecture teams to develop automated, scalable solutions. Allocate approximately 60% of time to writing SQL and/or Looker code for reporting, custom analyses, code review, and strategic analytics initiatives; 20% collaborating with team members and cross-functional departments; and 20% communicating analytical results verbally and in writing to stakeholders. Key Qualifications Minimum 8 years of experience in healthcare analytics with a specific focus on healthcare claims data, population health, and member experience. Deep understanding of the claims lifecycle and the nuances involved in reporting logic. Proven ability to write and optimize complex SQL queries for large-scale healthcare data environments. Experience building visualizations and models in Looker or comparable BI tools such as Tableau. Demonstrated track record of mastering new data environments and complex healthcare schemas with minimal training. Experience replacing manual hand-offs and processes with automated triggers or self-serve tools. Proven ability to identify underlying data commonalities across a portfolio of requests to maximize the impact of every tool or dashboard built. Proficiency in Agile project management tools including Jira for task management and Confluence for process documentation. Strong ability to communicate technical findings clearly to non-technical stakeholders and business context effectively to technical audiences. Bachelor's degree in Mathematics, Economics, Statistics, Computer Science, Business Administration, or a related quantitative field, or equivalent professional experience. Preferred Qualifications Direct experience working with healthcare claims and/or member experience data at a payer, provider, tech company, TPA, or point solution organization. AI-first mindset with demonstrated experience applying AI tools to analytics workflows or reporting pipelines. Experience operating as a senior individual contributor or technical lead in a fast-paced, client-facing analytics environment.

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