Software Architect_Data Scientist

Required Skills 8+ years of experience in a data scientist, ML engineer, or advanced analytics role Strong foundation in statistics — hypothesis testing, regression, time series analysis, Bayesian methods Advanced SQL — comfortable writing complex queries across large, multi-source datasets. Proficiency in Python or R for analysis, modeling, and automation Experience with ML/statistical libraries (scikit-learn, statsmodels, pandas, NumPy, or similar) Experience with AWS data and ML services (SageMaker, Redshift, Athena, Glue,QuickSight, or similar) Hands-on experience with Tableau Demonstrated ability to define metrics frameworks and build dashboards from scratch, not just maintain existing ones Experience building anomaly detection or predictive models in a production or operational context Key Responsibilities: Define and build the metrics framework for the digital ordering pipeline — from order intake through result delivery Design and deliver dashboards that track order volume, throughput, turnaround times, error rates, and system stability across multiple integration points Build predictive models to forecast order failures, volume trends, and capacity needs Develop automated anomaly detection to surface pipeline issues before they escalate Apply statistical methods for root cause analysis — diagnosing why systems fail, not just what failed Partner with engineering teams to instrument data collection where gaps exist Translate complex technical and statistical findings into clear narratives for executive leadership, engineering management, and individual engineering teams