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# Data Analyst

- **Company:** Rvo Health
- **Location:** Fort Mill, SC, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $70,000.0 - $95,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Big Data, BigQuery, Cloud Database, Software Quality, Data Transformation, Data Mining, Data Visualization, Database Queries, Python (Programming Language), Power BI, Software Tools, SQL Databases, Tableau (Software), Snowflake, Prompt Engineering, AI Coding Agents, Data Layers, Information Technology, Looker Analytics, Amazon Redshift
- **Published:** October 28, 2026
- **Apply:** https://startup.jobs/data-analyst-rvo-health-10591588

## About the Role

Required:

 * Bachelor's degree in a quantitative field (e.g., data science, statistics, computer science) or equivalent experience.
 * Proven experience in data analysis, modeling, visualization, and reporting.
 * Excellent analytical and problem-solving abilities.
 * Strong attention to detail and ability to work with complex datasets.
 * Effective communication and collaboration skills.
 * Ability to handle multiple projects and meet deadlines.
 * 2+ years of advanced proficiency in SQL for data extraction, manipulation, and analysis.
 * Proficiency in cleaning and shaping data with modeling tools (e.g. SQL, DBT, LookML).
 * Experience with data visualization tools (e.g., Tableau, Looker, Power BI) and database querying.
 * Hands-on experience with one or more cloud-based data warehousing platform (e.g. Big Query, Snowflake, Redshift).

Preferred:

 * Experience with Python or R for statistical analysis and automation.
 * Hands-on experience with data transformation, data modeling, and semantic definitions (e.g., dbt, LookML, or modular SQL).
 * Strong statistical analysis skills and knowledge of statistical techniques.
 * Comfort navigating ambiguity- capable of structuring messy data and formulating sound recommendations under conditions of uncertainty.
 * Familiarity with leveraging AI tooling/coding assistants to augment workflow velocity without compromising accuracy or code quality.

## Description

As a Data Analyst for Optum Perks, you won't be a ticket-taker waiting for sanitized specs or maintaining legacy dashboards. You will be an embedded analytical partner driving end-to-end strategic problem-solving within a high-growth, fast-evolving business unit. You'll be surrounded by a high-performing team of data practitioners and cross-functional leaders, providing an environment rich with mentorship, technical challenge, and clear runway for long-term professional growth.

We believe the best analysts are entrepreneurial: you are given the strategic opportunity (the "what") and empowered with the autonomy to design, build, and execute the solution (the "how").

This role spans the entire analytical lifecycle. On one end, you will establish and maintain durable single-source-of-truth reporting suites, automate routine workflows, and engineer resilient data models (dbt/semantic layers). On the other, you'll tackle high-leverage strategic problems-designing and implementing decision engines, evaluating on-site testing and experiments, unpacking complex customer unit economics (like LTV, retention, and churn), and optimizing commercial growth strategies.

Sitting directly between technical engineering and executive business leadership, you will instrument tracking upstream, leverage AI tooling to accelerate delivery, and turn complex behavioral data into actionable operational and product strategy., * Project Ownership & Autonomy: Lead end-to-end analytical projects: autonomously conduct requirement gathering with cross-functional stakeholders, define project milestones, and translate ambiguous business problems into structured analytical roadmaps.

 * Analytics & Context Engineering: Design, model, and maintain scalable datasets and semantic layers (e.g., via dbt, SQL) to establish trusted "single source of truth" tables for sustained reporting and agentic workflows.
 * Ambiguity & Decision-Making: Navigate incomplete or messy datasets with strong critical thinking, forming grounded assumptions and delivering clear, actionable recommendations to business partners.
 * Modern Tooling & AI: Leverage modern analytics tooling and AI coding assistants to accelerate development workflows, maintaining rigorous oversight, validation, and testing of all outputs.
 * Stakeholder Partnership: Interface upstream with data/software engineers to communicate tracking and infrastructure requirements, and communicate downstream with business leaders to translate findings into executive-level narratives and actionable business steps.