About
Basic Qualifications: A minimum of three years developing and deploying large scale advanced analytics applications into a production environment Minimum of five years, hands-on experience collaboratively developing code in object-oriented language for a production environment, including: Experience working in Linux environment (bash scripting) SQL (Data Normalization) Python Data Structures (arrays, lists, stacks, queues, trees, dictionaries, etc.) Experience in data mining techniques and methodologies (data prep/modeling, classification, regression, clustering, causal modeling, AI, machine learning, ensemble approaches) Advanced experience in data visualization tools with a strong grasp of effective data modeling and visualization practices Experience rapidly developing proof of concepts and testing new ideas, as well as scale these ideas into production ready models Experience leveraging cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure Preferred Qualifications: Advanced, relevant education, advanced Degree (Masters or PhD) in engineering, mathematics, physics, economics, computer science, statistics, or business analytics Experience with AWS big data services (Kinesis, Glue, EMR, Spectrum etc.) Experience with ETL & analytics tools (AWS, Matillion, Tallend, AtScale, etc.) Experience with data virtualization technologies (Denodo, etc.) Experience with data visualization tools (PowerBI, Tableau, etc.) Experience with Scrum/Agile delivery processes and DevOps concepts (i.e. CI/CD) Experience with data storage technologies (Redshift, S3, Hadoop, Graph, etc.) Experience with cloud Platforms (AWS, Azure, Google) Experience with multiple languages and syntax (Python, SQL, Apache Spark, etc.) Experience with Container based orchestration of big data pipelines
Languages
- English
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