Data Analyst Summer Intern at Care Indeed

, , -

Full Time

Start Date

Immediate

Expiry Date

12 Oct, 26

Salary

35.0

Posted On

14 Jul, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Cleaning, Exploratory Data Analysis, Data Visualization, R, Python, SQL, Looker, Power BI, Stakeholder Discovery, Metric Definition, Technical Documentation, Wireframing, Quantitative Analysis, Healthcare Data Privacy, AI-Supported Analysis

Industry

Individual and Family Services

Description

REPORTS TO: Senior Product Manager DEPARTMENT: Systems FLSA STATUS: Non-exempt LOCATION: Hybrid, primarily remote with visits to the Menlo Park or Campbell office as needed for in-person discovery ABOUT US Care Indeed delivers high-quality in-home senior care throughout the San Francisco Bay Area. Founded in 2010 by two care professionals, we have grown to over 700 employees dedicated to compassionate, reliable, and innovative care. For over 15 years, Care Indeed has supported seniors and families with personalized in-home care, memory care, skilled nursing, and 24/7 services that promote independence, dignity, and quality of life. We have served more than 5,000 clients, completed over 10,000 care shifts, and partnered with 100+ healthcare facilities across the region, demonstrating our community impact. Our caregivers and clinical staff deliver exceptional care daily, supporting each other within a culture of compassion, accountability, respect, and excellence. We’re proud to be recognized as: * One of Fortune’s Best Workplaces in Aging Services * A San Francisco Chronicle Top Workplace * A Best of Home Care – Employer of Choice and Leader in Experience POSITION OVERVIEW The Data Analyst Summer Intern will turn messy operational reality into trusted, production-ready dashboards, a decision playbook, and a QA triage workflow so leaders and QA can act early—without relying on ad hoc spreadsheets or ungoverned AI outputs. The intern contributes discovery, analysis, metric definitions, specifications, documentation, and supervised build work in partnership with Product, Data Engineering, Systems (Salesforce / AlayaCare / Looker as scoped), and department KPI owners. DUTIES & RESPONSIBILITIES 1. Stakeholder discovery & prioritization * Partner with Operations, QA, Clinical leadership, HR, Client Services, and other departments to understand decisions that should be informed by data. * Maintain a prioritized backlog of dashboard and metric requests: problem, user, decision, refresh cadence, and owner for sign-off. 2. Metrics, definitions & validation * Draft and iterate a metric dictionary (v1) for agreed measures: definition, grain (e.g. client, visit, case, caregiver), source system, limitations, and change log when definitions shift (e.g. post-migration). * Propose thresholds, weighted composites, or segmentation only where grounded in stakeholder input; include validation plans (distributions, time comparisons, spike reviews) and criteria for when to revise a metric. * Call out privacy, fairness, and workforce implications (especially for caregiver- or client-facing internal metrics) and align with company policy before production use. 3. Dashboards & reporting * Produce wireframes / specs for ~six production Looker dashboards aligned to each department’s primary KPIs (exact departments set in week 1–2 with manager), subject to access and migration reality. Include, as a priority lane, supply–demand / match views sourced from AlayaCare and implemented in Looker per company direction. * Support Power BI (or other agreed tools) only where explicitly approved for a given use case. * Work with Data Engineering on SQL (or approved Python/R analysis paths) when answers require querying databases beyond pre-built tiles. * Coordinate with Systems on AlayaCare / Looker / Salesforce implementation, permissions, and release per then-current ownership. 4. Decision playbook & QA triage * Deliver a concise decision playbook: how to read each KPI family, what “good” and “investigate” look like, common false positives, and who acts on what signal. * Document a QA triage workflow tied to the dashboards: outliers, drill-down paths (e.g. visit / caregiver / client), escalation, and links to operational policy where applicable. 5. AI-supported analysis (where appropriate — policy-bound) * Standard: Use approved internal AI tools to accelerate drafting, exploration, and QA prep; all metrics that drive decisions remain human-reviewed and traceable to Looker/SQL sources. * Where approved, support draft exploration using internal AI tools (primarily Claude via API access since that is under BAA and other access is not) on policy-compliant datasets, with human review required before any action affecting clients or caregivers. QUALIFICATIONS Required * Currently enrolled in (or recent graduate of) a quantitative program (e.g. data science, statistics, applied math, data theory, economics with heavy metrics). * Demonstrated experience with data cleaning, exploratory analysis, and visualization (coursework, internship, club consulting, or personal projects). * Strong skills in R and/or Python; comfort with SQL or willingness to learn quickly with mandatory code review from Data Engineering. * Excellent written and verbal communication; comfortable with non-technical stakeholders and iterative feedback. * Genuine interest in health services, aging, gerontology, or home-based care. Preferred * Experience with Power BI; exposure to Looker or BI embedded in clinical/ops platforms. * Experience reconciling multiple data sources or messy operational exports. * Coursework or projects in regression, probability, or experimental / validation thinking. * Prior exposure to healthcare privacy norms and responsible use of AI (human-in-the-loop, QA and validation of outputs). OUTCOMES (success by end of summer) 1. Subject to access, migration timing, and agreed supervision: 2. ~4-6 production Looker dashboards for department primary KPIs (with written specs for any item deferred to Systems backlog). 3. Decision playbook for interpreting and acting on those metrics. 4. QA triage workflow aligned to the dashboards. 5. Metric dictionary v1 and handoff notes for ongoing ownership post-internship. LOCATION & SCHEDULE * Location: Hybrid preferred (Menlo Park, CA) with flexibility for fully remote if agreed. * Timing: Roughly 5 weeks, 32–40 hours per week—exact start/end by mutual agreement and school constraints. * Supervision (starting assumption): ~2 hours/week with hiring manager (Senior PM); additional time from Systems, Engineering, and department KPI owners as agreed for implementation and sign-off. WORKING NORMS & PARTNERS * Technical QA: Data Engineering for SQL, warehouse logic, and data quality. * Systems: AlayaCare administration; Salesforce reporting; Looker build/admin within AlayaCare; Power BI if needed. * Confidentiality: All work on client and workforce data follows Care Indeed policies, training, and least-privilege access. COMPENSATION & BENEFITS * Paid internship CULTURE & IMPACT * A mission-driven organization grounded in compassion, accountability, respect, and excellence * A workplace consistently recognized as a Best Place to Work in Aging Services EQUAL OPPORTUNITY & ACCOMMODATION Care Indeed is an equal opportunity employer. We encourage all qualified applicants to apply and value diversity in our workforce, just as the clients and families we serve are diverse. Care Indeed provides reasonable accommodations in accordance with federal, state, and local law. Applicants who require assistance or accommodation during the application or employment process may contact HumanResources@careindeed.com. Make an Impact. Join Our Team. Apply at https://careindeed.com/careers [https://careindeed.com/careers?utm_source=chatgpt.com] or call 650-563-8711 to learn more.

Responsibilities

The intern will develop production-ready dashboards, a metric dictionary, and a decision playbook to improve operational data visibility. They will partner with various departments to define KPIs and implement reporting workflows using Looker and SQL.