Vice President

  • 39042
  • Non-Life - Data Science
  • |
  • New York, United States
  • |
  • Feb 4, 2021
Reinsurance
RESPONSIBILITIES
  • Design and build scalable infrastructure and platform to ingest, store and process very large amounts of data (structured, semi-structured and unstructured), including streaming and real-time into the cloud based Big Data Lake
  • Build best in class ETL/ELT based solutions for effective data ingestion and transformation
  • Collaborate with the various technical, platform and product development team on the use of various AWS services, including Amazon Elastic Compute Cloud (EC2), S3, Elastic Map Reduce (EMR), etc.
  • Work closely with the IT and the platform team to deliver technical solutions. This includes end to end data orchestration, data layering, data governance, metadata management and data cataloging
  • Be an expert in all things data including data wrangling, aggregation, summarization and analysis
  • Collaborate with the various data source teams both internal and external (Oracle, Teradata etc.) on effective strategies for data ingestion Partner with the data science, actuarial science and various business group on deep rooted data analysis including propensity scores, catastrophic modeling, time-series analysis and forecasting
  • Be an evangelist for all things Big Data and Digital
QUALIFICATIONS
  • Bachelor’s Degree in Computer Science, Mathematics, Engineering or Statistics. Master’s Degree a definite plus
  • 5-10 years of overall data, systems development and integration experience
  • 2-5 years of relevant Data Ingestion/ETL/ELT, Big Data and Data Visualizations experience of mission critical platforms
  • Experience in ETL/ELT and data wrangling using tools (Informatica, Talend etc.) and languages such as Python, R, Scala, Java, SQL and SAS
  • Experience in Hadoop and Big Data platforms including cloud based platforms such as AWS, Azure & GCP.
  • Experience in various services such as Hive, EMR, Juypter notebooks, Kinesis, etc.
  • Knowledge of Statistics, Operations Research and Machine/Deep Learning algorithms a definite plus
  • Ability to work in a fast-paced environment both as an individual contributor and a technical lead
  • Prior hands-on experience delivering self-service big data and data visualization platforms