Operations Data Analyst II

Job not on LinkedIn

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🏄 California – Remote

🏄 California – Remote

💵 $100k - $150k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Gold Coast Health Plan

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2011

At Gold Coast Health Plan, we are driven to create the health plan of the future - today. We are disrupting the conventions of the health care industry by creating and applying leading-edge solutions to its many challenges.

📋 Description

• Perform advanced statistical and quantitative analysis of healthcare, operational, claims, encounter, membership, and enterprise data • Develop statistical models and algorithms to identify anomalies, patterns, trends, risks, and opportunities • Apply regression, hypothesis testing, forecasting, segmentation, outlier detection, trend analysis, and other quantitative techniques • Develop and maintain analytical solutions using SQL, Python, R, Power BI, and other approved tools • Serve as analytical owner or subject matter resource for assigned operational domains • Develop dashboards, reports, data visualizations, and analytical products translating complex information into actionable business insights • Automate recurring analytical processes, regulatory metrics, operational KPIs, and data validation activities • Analyze complex datasets, identify relationships, trends, data-quality issues, and improvement opportunities • Perform data profiling, validation, reconciliation, and quality analysis • Develop and maintain data models, analytical datasets, data definitions, and source-to-target mapping documentation • Partner with stakeholders to define analytical questions, methodologies, success measures, and business recommendations • Collaborate with IT, Enterprise Analytics, developers, data engineers, consultants, and technical resources • Support enterprise data warehouse solutions, including Microsoft Azure Synapse • Develop analytical solutions for Grievances & Appeals, Encounters, Risk Adjustment, Claims, Membership, and related functions • Evaluate claims and encounter patterns and anomalies indicating operational issues, payment variation, data-quality concerns, or investigation opportunities • Measure operational performance, identify statistically significant variation, and evaluate operational interventions • Perform exploratory data analysis for new models, measures, and decision-support tools • Document methodologies, assumptions, limitations, data sources, and results • Present complex analytical findings to technical and non-technical audiences • Provide guidance and technical support to Data Analyst I staff and Operations Analytics team members • Participate in cross-functional projects and enterprise initiatives • Recommend improvements to analytical capabilities and ensure solutions meet business and regulatory requirements • Perform other duties as assigned

🎯 Requirements

• Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Information Systems, Business Analytics, or another quantitative or related field, or equivalent qualifying experience • 5+ years of progressively responsible experience in data analysis, statistical analysis, business intelligence, or related analytical work • Alternatively, 9+ years of progressively responsible experience in related analytical work in lieu of a degree • Complex SQL queries and relational databases • Reports, dashboards, or analytical solutions using Power BI or another data visualization platform • Statistical methods applied to business or operational problems • Advanced SQL/T-SQL • Advanced Microsoft Office skills • Ability to apply quantitative and statistical methods to complex business problems • Ability to select appropriate analytical methodologies and evaluate statistical results • Ability to communicate complex analytical concepts to technical and non-technical audiences • Ability to document analytical methods, findings, assumptions, and recommendations • Ability to work effectively across departments and disciplines