Lead Analyst, Analytics
Job description
About the role
Enterprise analytics steer strategy and elevate healthcare outcomes, and this role drives high-impact value-based care analysis. You will translate complex healthcare data into strategic insights that influence executive decision-making and policy formation. This position requires a blend of statistical rigor, technical curiosity, and business acumen to solve critical problems in value-based care. The role emphasizes the transformation of raw clinical and operational data into narratives that improve patient outcomes. You will act as a bridge between technical teams and senior leadership to ensure analysis drives action. Success in this role is defined by the ability to turn ambiguous questions into measurable results. Your work will directly support the strategic goals of improving care quality and operational efficiency.
Key facts
What you'll do
Investigate complex healthcare datasets to uncover trends in utilization, costs, and clinical outcomes for value-based care programs.
Develop and maintain interactive dashboards that visualize key performance indicators for diverse stakeholders across the organization.
Design SQL queries to extract, transform, and validate data from multiple sources to ensure accuracy and reliability of analytical outputs.
Collaborate with cross-functional partners to define metrics, scope analyses, and translate business needs into technical specifications.
Conduct statistical analyses to evaluate program effectiveness and identify opportunities for optimization in care delivery.
Build and iterate data models that support predictive and prescriptive analytics for strategic planning and resource allocation.
Document analytical processes and assumptions to ensure reproducibility, transparency, and knowledge transfer across the team.
Partner with data engineers to improve data infrastructure, focusing on scalability, performance, and data quality in analytical pipelines.
Lead the interpretation of experimental results and observational studies to inform decision-making and guide strategic recommendations.
Present findings to executive audiences, emphasizing actionable insights, risk assessment, and the business impact of proposed changes.
Requirements
A bachelor's degree is required as a baseline for this role, though the specific field is confirmed Candidates must possess strong analytical skills and the ability to manipulate large datasets to derive meaningful conclusions.
Proficiency with SQL and data querying languages is essential for accessing and transforming complex healthcare data.
Experience with data visualization tools is required to communicate findings effectively to both technical and non-technical stakeholders.
The role demands comfort with statistical methods to analyze trends, run experiments, and interpret results accurately.
You must demonstrate the ability to work independently and manage multiple analytical projects in a fast-paced environment.
Excellent written and verbal communication skills are necessary to explain technical concepts to diverse audiences.
A proven track record of using data to drive decisions is required, showing that your analysis has led to tangible improvements.
Nice to have
Healthcare domain expertise translates data into meaningful action for diverse stakeholders.
Skills & tools
Structured data methods turn complexity into clear direction. Data teams rely on dashboards, models, and pipelines.
Practical notes
Typical interview steps
Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.
Nice to have
Healthcare domain expertise translates data into meaningful action for diverse stakeholders.
Skills & tools
Structured data methods turn complexity into clear direction. Data teams rely on dashboards, models, and pipelines.
Good to know
Analytics professionals translate numbers into decisions, and portfolios of past analyses often outweigh degrees. Modern roles depend on scalable platforms and close collaboration with business teams. Continuous learning is essential in a field shaped by evolving standards and tools. Work typically involves SQL, statistical interpretation, and case-based problem solving. Clear communication of uncertainty and business impact is a common expectation in interviews.
Questions to ask
Useful questions for the interview: what a typical week looks like, how work is assigned, what tools the team uses, and how feedback works. Asking how the role has changed recently and what the team wishes it had known when joining is also reasonable. Questions about the manager's priorities are especially valued.
Career growth
Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.
About the company
About the location
Remote (USA) roles allow working from any eligible location within the United States.
About the company
Arcadia Group Ltd was a British multinational retailing company headquartered in London, England. It was best known for being the previous parent company of British Home Stores (BHS), Burton, Dorothy Perkins, Debenhams, Evans, Miss Selfridge, Topman, Topshop, Wallis and Warehouse.