Data Science, Analytics & MLOps
Transform raw telemetry into institutional foresight. We architect resilient data pipelines, deploy explainable machine learning models, and build real-time executive decision systems.
From Raw Telemetry to High-Confidence Foresight
We combine deep mathematical rigor with industrial-scale data engineering to ensure models perform accurately in high-velocity production environments.
Predictive Modelling & Automated Pipelines
End-to-end machine learning from raw data lakes to production inference endpoints — automated feature engineering, continuous retraining pipelines, model drift alerting, and explainability scorecards.
- High-accuracy classification, regression, and complex time-series forecasting
- Gradient boosting optimization with XGBoost, LightGBM, and CatBoost
- Automated experimentation, model registry, and lifecycle tracking via MLflow
- Model interpretability and feature attribution scorecards with SHAP and LIME
High-Throughput Streaming & Data Warehouses
Architect the resilient data foundations your analytical models depend upon — scalable real-time streaming architectures, batch pipelines, and medallion cloud warehouses.
- Distributed stream processing with Apache Spark, Kafka, and Flink
- dbt-orchestrated transformation layers over Snowflake, BigQuery, and Databricks
- Automated data quality testing and anomaly isolation with Great Expectations
- Enterprise Medallion lakehouse architecture (Bronze raw → Silver clean → Gold aggregated)
Executive Dashboards & Decision Intelligence
Transform complex petabyte-scale data lakes into responsive, board-ready visualization suites — providing real-time KPI telemetry, predictive alerting, and self-service analytics.
- Production enterprise dashboards in Tableau, Power BI, and Looker
- Custom white-labeled analytics embedded into customer-facing portals
- Sub-second streaming metrics via WebSocket feeds and time-series stores
- Drill-through operational reports with automated alerting and anomaly flags
Statistical Causal Inference & Fraud Detection
Move beyond simple correlation to understand true causality — multi-armed bandit experimentation, causal uplift modeling, and high-velocity fraud pattern recognition.
- Bayesian A/B testing platforms and continuous bandit optimization
- Causal inference and counterfactual policy analysis using DoWhy and EconML
- Customer lifetime value, cohort survival analysis, and churn prevention
- Real-time graph analytics for fraud ring discovery and transaction anomalies
Enterprise Data Governance & High-Availability Architecture
Enterprise Data Lineage & Hygiene
Automated tracking of data provenance from source ingestion to BI dashboards, ensuring audit-compliant transformations and zero silent data corruption.
Sub-Second Ingestion & Real-Time Querying
Optimized columnar indexing, distributed partitioning, and in-memory caches delivering sub-second queries over billions of transactional records.
Regulatory Privacy & RBAC Segregation
Column-level masking, automated PII anonymization, and granular role-based access controls fully aligned with GDPR, DPDPA, and HIPAA mandates.
From Data Discovery to Continuous Model Serving
Data Audit & Architecture
Audit source telemetry, evaluate data hygiene, and map analytical goals to high-leverage business metrics.
Pipeline & Lakehouse Build
Construct reproducible streaming and batch ETL pipelines feeding structured medallion data layers.
Model Training & Validation
Engineer domain features, train candidate algorithms, validate cross-fold metrics, and explain outcomes.
Production Serving & MLOps
Deploy low-latency inference endpoints backed by automated drift monitoring and scheduled retraining cycles.
Ready to build your next software initiative with embedded security?
Whether you are preparing for enterprise compliance audits, refactoring critical cloud infrastructure, or launching a brand-new application — MAGEN delivers sovereign-grade engineering practices tailored to your sector's most pressing requirements.