[Hybrid_HN]_Data Analyst

Scope of work

We are hiring Data Specialists with deep experience in health analytics and a strong track record of delivering impactful, scalable analytical solutions. This role is designed for a strong individual contributor who can operate as an analytics builder - independently owning complex workstreams, designing durable data-driven systems, and influencing decisions across business, clinical, operational, data science, and technology teams. The ideal candidate brings strong healthcare domain knowledge, deep analytical thinking, hands-on experience with large and complex datasets, working knowledge of machine learning concepts, and an AI-native working style. The role may involve guiding junior analysts or a small analytics pod, but the primary expectation is hands-on ownership and high-quality individual delivery.

Key Responsibilities

• Lead health analytics initiatives across areas such as claims, clinical operations, member analytics, provider performance, population health, care management, medical cost, utilization, quality, or outcomes analytics.
• Translate ambiguous healthcare and business problems into structured analytical approaches with clear metrics, hypotheses, and decision frameworks.
• Design, architect, and implement scalable, big data-driven analytics systems, reusable data assets, dashboards, insight engines, and decision-support tools.
• Work with large-scale healthcare datasets, including claims, clinical, member, provider, operational, utilization, cost, and outcomes data.
• Apply deep analytical thinking to identify patterns, root causes, risks, opportunities, and actionable insights.
• Use AI-assisted tools effectively to multiply productivity across analysis, coding, documentation, insight generation, and stakeholder communication.
• Collaborate with Data Scientists and ML teams on advanced analytics use cases, including feature design, model evaluation, business validation, and interpretation of model outputs.
• Partner with business, clinical, product, operations, finance, engineering, and technology stakeholders to ensure solutions are practical, trusted, and adopted.
• Where required, guide junior analysts by reviewing work, shaping analytical approaches, and raising delivery quality

Recruitment

Required Qualifications

• 5+ years of experience in health analytics, healthcare data analytics, or related analytical roles within payer, provider, health-tech, insurance, life sciences, or healthcare consulting environments.
• Deep understanding of healthcare data, business processes, and analytical use cases.
• Strong analytical thinking with the ability to break down complex problems and produce actionable insights.
• Proven ability to architect and implement impactful, long-running, big data-driven analytics systems or data products.
• Strong individual contributor mindset with the ability to independently own complex analytical problems from definition to delivery.
• Demonstrated ability to operate as an analytics builder, creating reusable, scalable analytical assets rather than one-off reports.
• AI-native working style, with proven ability to use AI-assisted tooling to improve productivity and delivery quality.
• Strong hands-on experience working with large, complex, and messy datasets.
• Advanced proficiency in Python and PySpark.
• Working knowledge of machine learning concepts, including feature engineering, model outputs, evaluation metrics, and practical business application of ML models.
• Excellent communication and stakeholder management skills, with the ability to influence decisions using data.

Preferred Qualifications

• Experience in payer analytics, provider analytics, population health, value-based care, care management, claims analytics, medical cost analytics, quality analytics, or clinical operations analytics.
• Familiarity with healthcare data standards or coding systems such as ICD, CPT, DRG, SNOMED, LOINC, HEDIS, or risk adjustment.
• Hands-on experience with big data platforms such as Databricks, Spark, cloud data lakes, Azure, AWS, or equivalent environments.
• Experience building analytics products or systems used repeatedly by business, clinical, or operational teams.
• Experience guiding or mentoring junior analysts is a plus.
• Proficient in English

What Good Looks Like

• A strong analytics builder who can turn ambiguity into durable, high-impact analytical systems.
• Deep healthcare analytics expertise with strong business context.
• High ownership mindset with focus on impact, data quality, and stakeholder trust.
• AI-native approach to working faster, improving quality, and increasing leverage.
• Ability to collaborate closely with Data Science teams and translate model outputs into business-ready insights