{"title":"Data Analyst Claude Skills","description":"\u003cp\u003eClaude skills for data analysts. Downloadable .md configuration files that make Claude read a dataset the way an analyst does: check the shape of the data first, pick the right cut, and explain what the numbers actually support. Instant download, 30-day money-back guarantee.\u003c\/p\u003e","products":[{"product_id":"clara-data-analyst-ai-skill","title":"Clara - Data Analyst AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n\n  \u003cp style=\"font-size: 16px; font-weight: 600; color: #1A1A18; line-height: 1.5; margin: 0 0 8px 0;\"\u003e\n    Drop Clara into Claude and get a Data Analyst who turns raw data into clear, actionable insights - defining the analytical question, assessing data quality, producing exploratory analysis, writing Excel and SQL formulas, interpreting statistical results in plain English, and communicating findings as a clear story with a \"so what\" and a recommended action.\n  \u003c\/p\u003e\n\n  \u003cp style=\"font-size: 13px; font-weight: 400; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003e\n    Clara is one of the most analytically honest AI data tools available in Claude format - built for marketing teams, finance functions, HR analysts, product teams, and students across every industry where data needs to become a decision. She never implies causation from correlation, always flags statistical caveats, and is explicit about the limits of what small samples, missing data, or selection bias allow you to conclude. Analysis without data context produces wrong answers - she always asks what the data contains, how it was collected, and what you are trying to answer before touching a single number.\n  \u003c\/p\u003e\n\n  \u003cdiv style=\"background: #E8F6F9; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #1A8FA8; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n      \u003cli style=\"font-size: 13px; color: #1A1A18; padding: 7px 0; border-bottom: 1px solid rgba(26,143,168,0.12); display: flex; align-items: flex-start; gap: 10px;\"\u003e\n        \u003cspan style=\"color: #1A8FA8; font-weight: 600; flex-shrink: 0;\"\u003e→\u003c\/span\u003e\n        \u003cspan\u003eAnalytical question definition and data quality assessment - precise question framing from business or research problems, data completeness and consistency checks, identification of what can and cannot be answered from available data, and honest flagging of limitations before analysis begins\u003c\/span\u003e\n      \u003c\/li\u003e\n      \u003cli style=\"font-size: 13px; color: #1A1A18; padding: 7px 0; border-bottom: 1px solid rgba(26,143,168,0.12); display: flex; align-items: flex-start; gap: 10px;\"\u003e\n        \u003cspan style=\"color: #1A8FA8; font-weight: 600; flex-shrink: 0;\"\u003e→\u003c\/span\u003e\n        \u003cspan\u003eExploratory data analysis - distributions, central tendencies, spread, outlier and anomaly detection, missing value identification, pattern and correlation identification, and initial findings that tell you what the data actually contains before jumping to conclusions\u003c\/span\u003e\n      \u003c\/li\u003e\n      \u003cli style=\"font-size: 13px; color: #1A1A18; padding: 7px 0; border-bottom: 1px solid rgba(26,143,168,0.12); display: flex; align-items: flex-start; gap: 10px;\"\u003e\n        \u003cspan style=\"color: #1A8FA8; font-weight: 600; flex-shrink: 0;\"\u003e→\u003c\/span\u003e\n        \u003cspan\u003eExcel, SQL, Python, and R guidance - Excel and Google Sheets formula writing (VLOOKUP, XLOOKUP, SUMIFS, pivot tables), SQL query writing and explanation for SELECT, GROUP BY, JOIN, and aggregate functions, Python pandas DataFrame operations and groupby, and R summary statistics for research data\u003c\/span\u003e\n      \u003c\/li\u003e\n      \u003cli style=\"font-size: 13px; color: #1A1A18; padding: 7px 0; border-bottom: 1px solid rgba(26,143,168,0.12); display: flex; align-items: flex-start; gap: 10px;\"\u003e\n        \u003cspan style=\"color: #1A8FA8; font-weight: 600; flex-shrink: 0;\"\u003e→\u003c\/span\u003e\n        \u003cspan\u003eStatistical interpretation in plain English - p-values, confidence intervals, and sample size explained in context, statistical significance vs practical significance distinguished, correlation vs causation enforced without exception, and A\/B test results interpreted correctly so decisions are made on real evidence\u003c\/span\u003e\n      \u003c\/li\u003e\n      \u003cli style=\"font-size: 13px; color: #1A1A18; padding: 7px 0; border-bottom: 1px solid rgba(26,143,168,0.12); display: flex; align-items: flex-start; gap: 10px;\"\u003e\n        \u003cspan style=\"color: #1A8FA8; font-weight: 600; flex-shrink: 0;\"\u003e→\u003c\/span\u003e\n        \u003cspan\u003eInsight communication - analytical findings structured as finding → evidence → implication → action, visualisation recommendations matched to data type and audience, and data commentary written so non-analysts understand what the numbers mean and what to do next\u003c\/span\u003e\n      \u003c\/li\u003e\n      \u003cli style=\"font-size: 13px; color: #1A1A18; padding: 7px 0; display: flex; align-items: flex-start; gap: 10px;\"\u003e\n        \u003cspan style=\"color: #1A8FA8; font-weight: 600; flex-shrink: 0;\"\u003e→\u003c\/span\u003e\n        \u003cspan\u003eIndustry-specific analysis - survey data (Likert scales, cross-tabs, response bias), financial data (revenue trends, margin analysis, variance commentary), marketing analytics (campaign performance, funnel analysis, attribution), HR analytics (survey results, retention, headcount), and academic dissertation data (descriptive statistics, results interpretation)\u003c\/span\u003e\n      \u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n\n  \u003cdiv style=\"display: flex; align-items: center; gap: 20px; background: #FFFFFF; border: 1px solid #E8E6E0; border-radius: 8px; padding: 14px 20px; margin-bottom: 24px;\"\u003e\n    \u003cspan style=\"font-size: 11px; color: #888780; font-family: monospace;\"\u003e📄 clara-data-analyst-ai-skill.skill\u003c\/span\u003e\n    \u003cdiv style=\"width: 1px; height: 16px; background: #E8E6E0;\"\u003e\u003c\/div\u003e\n    \u003cspan style=\"font-size: 11px; color: #888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cdiv style=\"width: 1px; height: 16px; background: #E8E6E0;\"\u003e\u003c\/div\u003e\n    \u003cspan style=\"font-size: 11px; color: #888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n\n  \u003cdiv style=\"border-left: 3px solid #1A8FA8; padding-left: 16px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #1A8FA8; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size: 12px; color: #555550; line-height: 1.7; margin: 0;\"\u003e\n      Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → share your data, describe the business question, and explain how the data was collected → Clara defines the question and produces structured analytical findings instantly.\n    \u003c\/p\u003e\n  \u003c\/div\u003e\n\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":57639969980680,"sku":"clara-data-analyst-ai-skill","price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/clara-data-analyst-book.jpg?v=1787064988"},{"product_id":"leila-data-scientist","title":"Leila - Data Scientist AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n  \u003cp style=\"font-size: 16px; font-weight: 600; line-height: 1.5; margin: 0 0 8px 0;\"\u003eDrop Leila into Claude and get a senior data scientist who frames the question, runs the right statistics, and designs A\/B tests that give trustworthy answers.\u003c\/p\u003e\n  \u003cp style=\"font-size: 13px; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003eLeila frames business problems, does rigorous EDA, applies the correct statistics and hypothesis tests, designs and analyzes A\/B tests (power, sample size, guardrails, SRM), builds regression and classification models, reasons about causality, and communicates the decision. Always validate assumptions on a representative sample, version the analysis, and review before acting in production.\u003c\/p\u003e\n  \u003cdiv style=\"background: #F8EAF4; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #C13AAE; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eFraming, EDA and the right statistical test\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eA\/B testing: power, sample size, guardrails, honest readout\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eRegression and classification modeling\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0;  display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eCausal inference basics and stakeholder communication\u003c\/span\u003e\n\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"display:flex; align-items:center; gap:20px; background:#FFFFFF; border:1px solid #E8E6E0; border-radius:8px; padding:14px 20px; margin-bottom:24px;\"\u003e\n    \u003cspan style=\"font-size:11px; color:#888780; font-family:monospace;\"\u003e📄 leila-data-scientist.skill\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"border-left:3px solid #C13AAE; padding-left:16px;\"\u003e\n    \u003cp style=\"font-size:10px; font-weight:600; color:#C13AAE; letter-spacing:0.08em; text-transform:uppercase; margin:0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size:12px; color:#555550; line-height:1.7; margin:0;\"\u003eDownload the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Leila builds the answer. Includes a full worked example so you see exactly what you get.\u003c\/p\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58300413214984,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/leila-data-scientist-book.jpg?v=1787064990"},{"product_id":"bram-analytics-engineer","title":"Bram - Analytics Engineer AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n  \u003cp style=\"font-size: 16px; font-weight: 600; line-height: 1.5; margin: 0 0 8px 0;\"\u003eDrop Bram into Claude and get a senior analytics engineer who builds tested, documented dbt models and dimensional marts on the modern data stack.\u003c\/p\u003e\n  \u003cp style=\"font-size: 13px; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003eBram builds the transformation layer: dbt models (staging → intermediate → marts), sources and freshness, tests, snapshots (SCD2), macros and Jinja, incremental models with the right strategy, exposures and the semantic layer, dimensional (Kimball) modeling, and CI\/CD for analytics. Always build in a dev target, run dbt tests, version in git, and review before promoting to production.\u003c\/p\u003e\n  \u003cdiv style=\"background: #F8EAF4; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #C13AAE; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003edbt models: staging → intermediate → marts, sources, freshness\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eTests, snapshots (SCD2), macros and Jinja\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eIncremental models with the right strategy\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0;  display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eKimball dimensional modeling and CI\/CD for analytics\u003c\/span\u003e\n\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"display:flex; align-items:center; gap:20px; background:#FFFFFF; border:1px solid #E8E6E0; border-radius:8px; padding:14px 20px; margin-bottom:24px;\"\u003e\n    \u003cspan style=\"font-size:11px; color:#888780; font-family:monospace;\"\u003e📄 bram-analytics-engineer.skill\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"border-left:3px solid #C13AAE; padding-left:16px;\"\u003e\n    \u003cp style=\"font-size:10px; font-weight:600; color:#C13AAE; letter-spacing:0.08em; text-transform:uppercase; margin:0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size:12px; color:#555550; line-height:1.7; margin:0;\"\u003eDownload the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Bram builds the answer. Includes a full worked example so you see exactly what you get.\u003c\/p\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58300414624008,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/bram-analytics-eng-book.jpg?v=1787064990"},{"product_id":"chiara-data-analyst","title":"Chiara - Data Analyst AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n  \u003cp style=\"font-size: 16px; font-weight: 600; line-height: 1.5; margin: 0 0 8px 0;\"\u003eDrop Chiara into Claude and get a senior data analyst who turns a fuzzy question into a precise SQL answer, with the metric defined and the caveats stated.\u003c\/p\u003e\n  \u003cp style=\"font-size: 13px; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003eChiara translates a business question into a query, writes SQL with joins, CTEs and window functions, defines metrics precisely to avoid double-counting, runs cohort\/retention and funnel analysis and segmentation, builds clear dashboards, and communicates the answer with caveats. Always sanity-check queries against known totals on a sample and document the metric before sharing.\u003c\/p\u003e\n  \u003cdiv style=\"background: #F8EAF4; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #C13AAE; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eSQL depth: joins, CTEs, window functions, date logic\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eMetric definitions without double-counting\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(193,58,174,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eCohort\/retention, funnel and segmentation analysis\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0;  display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#C13AAE; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eClear dashboards and caveated communication\u003c\/span\u003e\n\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"display:flex; align-items:center; gap:20px; background:#FFFFFF; border:1px solid #E8E6E0; border-radius:8px; padding:14px 20px; margin-bottom:24px;\"\u003e\n    \u003cspan style=\"font-size:11px; color:#888780; font-family:monospace;\"\u003e📄 chiara-data-analyst.skill\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"border-left:3px solid #C13AAE; padding-left:16px;\"\u003e\n    \u003cp style=\"font-size:10px; font-weight:600; color:#C13AAE; letter-spacing:0.08em; text-transform:uppercase; margin:0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size:12px; color:#555550; line-height:1.7; margin:0;\"\u003eDownload the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Chiara builds the answer. Includes a full worked example so you see exactly what you get.\u003c\/p\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58300415705352,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/chiara-data-analyst-book.jpg?v=1787064991"},{"product_id":"solveig-fraud-risk-data-analyst","title":"Solveig - Fraud \u0026 Risk Data Analyst AI Skill","description":"\u003ch2\u003eSenior Fraud \u0026amp; Risk Data Analyst who treats every detection rule as something actively being probed for its blind spot.\u003c\/h2\u003e\n\u003cp\u003eSolveig covers the full fraud and risk analytical surface: fraud signal and feature design (velocity checks, device fingerprinting, network and graph-based fraud rings), rule-based versus ML-based detection tradeoffs and when to combine them, false-positive versus false-negative cost tuning, chargeback and dispute pattern analysis, and adversarial adaptation as fraud patterns shift once a rule becomes known.\u003c\/p\u003e\n\u003ch3\u003eWho it's for\u003c\/h3\u003e\n\u003cp\u003eTrust-and-safety and payments teams who need fraud signals, thresholds, and rule-vs-model decisions tied to a named dollar cost, not a rule tuned on accuracy alone that quietly stops working the moment fraudsters notice it.\u003c\/p\u003e\n\u003ch3\u003eKey capabilities\u003c\/h3\u003e\n\u003cul\u003e\n      \u003cli\u003eVelocity, device, and network\/graph fraud signals tied to a specific named fraud pattern, not generic data\u003c\/li\u003e\n      \u003cli\u003eFalse-positive and false-negative costs named in dollars per segment before any threshold gets tuned\u003c\/li\u003e\n      \u003cli\u003eRule-based vs ML-based layering decided by adaptation speed and explainability need, not a default preference\u003c\/li\u003e\n      \u003cli\u003eChargeback and dispute pattern reports segmented by reason code, separating true fraud from friendly fraud\u003c\/li\u003e\n      \u003cli\u003eAdversarial adaptation monitoring that catches a known rule decaying once a fraud ring has gamed it\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eHow to use it\u003c\/h3\u003e\n\u003cp\u003ePaste Solveig's SKILL.md into your Claude Project Instructions (or any AI system prompt), then describe your Fraud \u0026amp; Risk Data Analyst problem. Works with Claude, ChatGPT, and any AI chat. Under 2 minutes to install.\u003c\/p\u003e\n","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58331107688712,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/solveig-fraud-risk-book.jpg?v=1787065048"},{"product_id":"ondine-infographic-dataviz-designer","title":"Ondine - Infographic \u0026 Data Visualization Designer AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n  \u003cp style=\"font-size: 16px; font-weight: 600; line-height: 1.5; margin: 0 0 8px 0;\"\u003eDrop Ondine into Claude and get a Senior Infographic \u0026amp; Data Visualization Designer who turns a dataset into a standalone visual built around the one claim it actually supports, not a pile of charts.\u003c\/p\u003e\n  \u003cp style=\"font-size: 13px; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003eOndine covers the full standalone infographic discipline: chart type selection matched to the shape of the comparison (part-to-whole, trend, ranked, correlation), information hierarchy design across complex datasets, editorial infographic layout with a real reading path, and icon and pictogram systems built specifically for data storytelling, always with an honest stated source.\u003c\/p\u003e\n  \u003cdiv style=\"background: #F8E7F5; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #A8248E; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(168,36,142,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#A8248E; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eChart type matched to the actual comparison type, never picked from habit\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(168,36,142,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#A8248E; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eInformation ranked into scan-tier and read-tier before layout starts\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(168,36,142,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#A8248E; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eA stated reading path instead of a grid of disconnected charts\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0;  display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#A8248E; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eIcon and pictogram systems built with consistent stroke weight and scale\u003c\/span\u003e\n\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"display:flex; align-items:center; gap:20px; background:#FFFFFF; border:1px solid #E8E6E0; border-radius:8px; padding:14px 20px; margin-bottom:24px;\"\u003e\n    \u003cspan style=\"font-size:11px; color:#888780; font-family:monospace;\"\u003e📄 ondine-infographic-dataviz-designer.skill\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"border-left:3px solid #A8248E; padding-left:16px;\"\u003e\n    \u003cp style=\"font-size:10px; font-weight:600; color:#A8248E; letter-spacing:0.08em; text-transform:uppercase; margin:0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size:12px; color:#555550; line-height:1.7; margin:0;\"\u003eDownload the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Ondine builds the answer. Includes a full worked example so you see exactly what you get.\u003c\/p\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58367806472456,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/ondine-infographic-dataviz-designer-book.jpg?v=1787132794"},{"product_id":"florian-epidemiology-public-health-data-analyst","title":"Florian - Epidemiology \u0026 Public Health Data Analyst AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n  \u003cp style=\"font-size: 16px; font-weight: 600; line-height: 1.5; margin: 0 0 8px 0;\"\u003eDrop Florian into Claude and get a Senior Epidemiology \u0026amp; Public Health Data Analyst who turns surveillance and outbreak data into statistically sound, decision-ready analysis.\u003c\/p\u003e\n  \u003cp style=\"font-size: 13px; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003eFlorian covers the full quantitative public health analysis cycle: disease surveillance signal detection with a stated case definition, outbreak investigation built on standard descriptive-then-analytic epidemiological structure, biostatistics matched to study design (odds ratios, relative risk, confounding adjustment), and dashboards tied to the decisions a health department actually needs to make, with confidence intervals and limitations stated on every finding.\u003c\/p\u003e\n  \u003cdiv style=\"background: #E7F8F5; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #1B7E6A; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(27,126,106,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#1B7E6A; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eCase definition stated explicitly before a single case gets counted\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(27,126,106,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#1B7E6A; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eReporting lag and denominator consistency checked before trusting any trend\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(27,126,106,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#1B7E6A; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eA named statistical method (control chart, CUSUM) behind every 'unusual' signal call\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0;  display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#1B7E6A; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eConfounding adjustment applied before presenting any comparison as definitive\u003c\/span\u003e\n\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"display:flex; align-items:center; gap:20px; background:#FFFFFF; border:1px solid #E8E6E0; border-radius:8px; padding:14px 20px; margin-bottom:24px;\"\u003e\n    \u003cspan style=\"font-size:11px; color:#888780; font-family:monospace;\"\u003e📄 florian-epidemiology-public-health-data-analyst.skill\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"border-left:3px solid #1B7E6A; padding-left:16px;\"\u003e\n    \u003cp style=\"font-size:10px; font-weight:600; color:#1B7E6A; letter-spacing:0.08em; text-transform:uppercase; margin:0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size:12px; color:#555550; line-height:1.7; margin:0;\"\u003eDownload the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Florian builds the answer. Includes a full worked example so you see exactly what you get.\u003c\/p\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58370408481032,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/florian-epidemiology-public-health-data-book.jpg?v=1787139934"},{"product_id":"oskari-geospatial-data-analyst","title":"Oskari - Geospatial Data Analyst AI Skill","description":"\u003cdiv style=\"font-family: 'DM Sans', sans-serif; color: #1A1A18; max-width: 680px;\"\u003e\n  \u003cp style=\"font-size: 16px; font-weight: 600; line-height: 1.5; margin: 0 0 8px 0;\"\u003eDrop Oskari into Claude and get a geospatial analyst who replaces the radius circle with a real drive-time isochrone and watches half the business case disappear.\u003c\/p\u003e\n  \u003cp style=\"font-size: 13px; color: #555550; line-height: 1.7; margin: 0 0 28px 0;\"\u003eOskari treats location as a first-class dimension: coordinate reference systems and projections and the quiet errors from getting them wrong; vector and raster data models; PostGIS, GeoPandas and warehouse-native geospatial functions; spatial joins, buffers, isochrones and drive-time analysis; geocoding and address normalization quality; spatial indexing with R-tree, H3, S2 and geohash and grid systems for aggregation; spatial statistics including spatial autocorrelation, Moran's I, hotspot analysis and the basics of kriging; trade-area and site-selection analysis; routing and network analysis; cartographic choices that mislead, such as unnormalized choropleths and bad binning; and the privacy risk in fine-grained location data.\u003c\/p\u003e\n  \u003cdiv style=\"background: #FAEBF5; border-radius: 12px; padding: 24px 28px; margin-bottom: 24px;\"\u003e\n    \u003cp style=\"font-size: 10px; font-weight: 600; color: #DA2FA1; letter-spacing: 0.08em; text-transform: uppercase; margin: 0 0 16px 0;\"\u003eWhat you get\u003c\/p\u003e\n    \u003cul style=\"margin: 0; padding: 0; list-style: none;\"\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(218,47,161,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#DA2FA1; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eCRS and projection correctness, geocoding quality\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(218,47,161,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#DA2FA1; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eSpatial joins, buffers, isochrones and drive-time trade areas\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0; border-bottom: 1px solid rgba(218,47,161,0.14); display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#DA2FA1; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eH3, S2 and geohash indexing plus spatial statistics\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli style=\"font-size: 13px; padding: 7px 0;  display: flex; gap: 10px;\"\u003e\n\u003cspan style=\"color:#DA2FA1; font-weight:600;\"\u003e→\u003c\/span\u003e\u003cspan\u003eHonest cartography and location-privacy risk\u003c\/span\u003e\n\u003c\/li\u003e\n    \u003c\/ul\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"display:flex; align-items:center; gap:20px; background:#FFFFFF; border:1px solid #E8E6E0; border-radius:8px; padding:14px 20px; margin-bottom:24px;\"\u003e\n    \u003cspan style=\"font-size:11px; color:#888780; font-family:monospace;\"\u003e📄 oskari-geospatial-data-analyst.skill\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eUnder 2 min install\u003c\/span\u003e\n    \u003cspan style=\"font-size:11px; color:#888780;\"\u003eWorks with Claude, ChatGPT \u0026amp; any AI chat\u003c\/span\u003e\n  \u003c\/div\u003e\n  \u003cdiv style=\"border-left:3px solid #DA2FA1; padding-left:16px;\"\u003e\n    \u003cp style=\"font-size:10px; font-weight:600; color:#DA2FA1; letter-spacing:0.08em; text-transform:uppercase; margin:0 0 6px 0;\"\u003eHow to install\u003c\/p\u003e\n    \u003cp style=\"font-size:12px; color:#555550; line-height:1.7; margin:0;\"\u003eDownload the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Oskari builds the answer. Includes a full worked example so you see exactly what you get.\u003c\/p\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e","brand":"KissMySkills","offers":[{"title":"Default Title","offer_id":58382361657608,"sku":null,"price":29.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1036\/1444\/7880\/files\/oskari-geospatial-book.jpg?v=1787065052"}],"url":"https:\/\/kissmyskills.com\/collections\/data-analyst-skills.oembed","provider":"KissMySkills","version":"1.0","type":"link"}