A full stack data science and big data practitioner with experience in the entire analytics project life cycle. This includes data science strategy, planning, scoping, problem framing, change management, requirement gathering, solution design, build, testing and deployment.

Value driven and able to plan and build prototypes to prove concepts, demonstrate return on investment, architect, build and productionize an enterprise scale data solution.

Areas of Technical Experience: Supervised and unsupervised machine learning methods, predictive modelling analytics, text analytics, data pre-processing, feature engineering and experimental design and predictive maintenance.

Big data architectures and the Hadoop ecosystem technologies (Hive, Ambari, Spark/PySpark, YARN, Mapreduce, HDInsight).

Distributed computing, cloud computing, SQL and NoSQl storage systems.

Microsoft Azure Suite of technologies (IoT Hub, Event Hub, Stream Analytics, Azure Function, Azure Storage, Cosmodb, Azure SQL database, PowerBI) and open source tools (Python, SQL, Javascript, Electron) for solution development.

Data integration, processing large, structured and unstructured data and developing pipelines for batch and streaming data processing.

Architecting and developing end-to-end Internet of things (IoT) solution using the Azure IoT suite.

Full stack software and web development experience.