Risk Adjustment Consulting, Experienced

Blue Shield of California•Oakland, CA

4d•Hybrid

About The Position

Your Role The Enterprise Retrospective Chart Review team oversees end to end retrospective coding operations, ensuring the accuracy, completeness, and compliance of medical record review across all risk adjusted lines of business. The team manages enterprise workflows, vendor performance, coding quality, audit readiness, and cross functional alignment with Clinical, Compliance, and Risk Adjustment partners.

Requirements

Requires a college degree or equivalent experience
Requires 3 years of prior relevant experience within healthcare, preferably Risk Adjustment
Requires practical knowledge of Risk Adjustment obtained through professional experience and advanced education
Requires familiarity with AI tools, including prompt engineering and workflow automation
Requires experience building dashboards or visual reports that support operational decision making
Requires strong communication skills for concise summaries and effective cross functional collaboration

Responsibilities

Analyze under the supervision of the core principles and functionality of decision and descriptive analytics including analyzing historical data, past performance and trends
Develop and run programs that apply to analytic decision techniques
Contribute to successful programs for the team, engaged in typically one area related to vendor oversight, internal cross functional partnerships, tracking performance and measuring results
Continuously learn about plan data including claim, premium, membership, and risk score assignment
Conduct data analysis, documenting and verifying the assumptions used in computations such as those used in member risk data and score submissions and establishing revenue accruals
Analyze operational performance to identify trends, risks, and improvement opportunities and to forecast retrieval volumes, coding workloads, and capacity needs using both traditional analytics and AI‑driven modeling
Design AI‑enabled workflows that enhance chart ingestion, data validation, and operational reporting for risk adjustment, using AI tools to improve efficiency and consistency
Automate data processes by building Python and SQL solutions and applying AI applications to streamline vendor file processing, recurring reporting, and ad hoc analytics
Produce operational reporting through dashboards and scorecards that summarize retrieval performance, coding outcomes, and risk adjustment trends, supported by AI‑assisted insight generation
Manage data quality by ingesting weekly vendor data loads, performing QA checks, validating accuracy, and applying AI tools to support anomaly detection and data review