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SQL for data extraction, transformation, exploratory analysis, with experience building reproducible analytical workflows. \nHands-on experience developing, validating or enhancing predictive, risk-scoring, fraud-detection or anomaly-detection models, including feature development, back-testing, threshold calibration and performance evaluation using measures such as precision, recall and related trade-offs. \nExperience translating business, policy or operational requirements into analytical specifications, model logic, indicators, rules or measurable risk hypotheses. \nExperience working with complex, large-scale datasets, including assessing data quality, tracing data lineage, investigating anomalies and documenting analytical assumptions. \nExperience handling the technical challenges to fraud or risk modelling, including imbalanced data and delayed, incomplete or evolving outcome labels. \nExperience designing or implementing production model-monitoring approaches, including data 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for interviews.\nTech Aalto Pte Ltd | 24S2130 EA | Pushpanjli Kir | R1657306.\nSkills\nInterSystems IRIS Data Platform, PySpark, AWS, Mathematics, Quantitative Analysis, XGBoost, MLOps, SQL, Python, CI/CD, Statistics, Data Science, Redshift","description_format":"text","description_chars":2606,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Recruiting & Staffing","IT Staffing & Staff Augmentation"],"lifecycle":[{"event":"open","at":"2026-10-28T10:28:00Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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