{"schemaVersion":"jobsearcher.job.v1","id":"7db077e94eaa90043d8d1d4f","url":"https://jobsearcher.com/jobs/7db077e94eaa90043d8d1d4f","canonicalUrl":"https://jobsearcher.com/jobs/7db077e94eaa90043d8d1d4f","title":"Data & Analytics (D&A) Developer II","description":"Job Title : Data & Analytics (D&A) Developer IILocation : 300 Garlington Road, Greenville, South Carolina, United States of America, 29615-4614Duration: 12+ months on W2 with possible extensionsJob Description -Required Technical SkillsCore Data Science & ML ToolsPython: Strong proficiency in data analysis, statistical modeling, and ML development (pandas, numpy, scikit-learn, scipy, curve fitting, object-oriented programming)Scenario Planning & What-If Analysis: Ability to build multi-scenario models to test assumptions and evaluate alternative planning outcomesMachine Learning: Foundational to intermediate experience with ML frameworks and methodologies (scikit-learn, XGBoost, or similar)Model Evaluation: Understanding of model validation metrics (R , MAE, RMSE, cross-validation, custom scoring functions)SQL: Proficiency in querying, joining tables, data manipulation, and interpreting complex queriesStatistical Analysis: Understanding of statistical modeling, hypothesis testing, and experimental designData Management CompetenciesData Exploration: Ability to independently explore enterprise datasets and identify patterns, gaps, and opportunitiesData Cleaning: Experience handling messy data, identifying inconsistencies, and standardizing formats across heterogeneous systemsData Integration: Experience merging multiple datasets from various enterprise data sources (SAP, Salesforce, Databricks, ERP/CRM)Anomaly Detection: Sharp eye for finding outliers, errors, and unusual patterns in structured and unstructured dataAI & Advanced AnalyticsSemantic Data Models: Understanding of data modeling concepts across heterogeneous systemsForecasting & Prediction: Experience developing models for scenario modeling and 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heterogeneous systemsData Integration: Experience merging multiple datasets from various enterprise data sources (SAP, Salesforce, Databricks, ERP/CRM)Anomaly Detection: Sharp eye for finding outliers, errors, and unusual patterns in structured and unstructured dataAI & Advanced AnalyticsSemantic Data Models: Understanding of data modeling concepts across heterogeneous systemsForecasting & Prediction: Experience developing models for scenario modeling and predictive use casesLarge Language Models (LLMs): Familiarity with LLMs and basic prompt engineering techniques for practical business applicationsDashboard & Logic ComprehensionReverse Engineering: Ability to review existing dashboards, ML models, and reports to understand design patterns, business requirements, and underlying data sourcesSQL Query Analysis: Strong capability to read and interpret complex SQL queries to understand data flows and business logicData Source Understanding: Skills to trace data lineage, review prepared 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