Data Analyst (Risk Domain)

Company: Synechron
Location: Jersey City, New Jersey, United States
Type: Full-time
Posted: 09.FEB.2021
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Summary

We (Synechron, Inc) are looking to hire for the role of Data Analyst (Risk Domain). This role is long-term and based in Jersey City, NJ/Char...

Description

We (Synechron, Inc) are looking to hire for the role of Data Analyst (Risk Domain). This role is long-term and based in Jersey City, NJ/Charlotte, NC.

About Synechron:

Synechron is one of the fastest-growing digital, business consulting & technology firms in the world. Headquartered in New York and with 22 offices around the world, Synechron is a leading Digital Transformation consulting firm and is working to Accelerate Digital initiatives for banks, asset managers, and insurance companies around the world. Synechron uniquely delivers these firms an end-to-end Digital, Consulting and Technology capabilities with expertise in wholesale banking, wealth management and insurance as well as emerging technologies like Blockchain, Artificial Intelligence, and Data Science. This has helped the company to grow to $650 Million+ in annual revenue and 10,000+ employees, and we're continuing to invest in research and development in the form of Accelerators (prototype applications) developed in our global Financial Innovation Labs (FinLabs).

Learn more at:

Job Description:

Role: Data Analyst (Risk Domain)

Work Location: Jersey City, NJ/Charlotte, NC

Duration: Long Term Project

  • Should have strong experience in Big Data skill sets ( Python, Spark, Scala, PySpark, SQL, Hive, Kafka etc )
  • Should have strong programming knowledge on Python, Spark to be applied to Big data environment.
  • Should have expertise in Informatica IDQ or any such similar tools.
  • Should have good experience in handing real time data ingestion into Big data environments
  • Should have good experience in building end to end data pipelines based on the Business requirements
  • Should have experience in implementing solutions On premise & also on Cloud environments.
  • Should have knowledge on Dev Ops implementations
  • Should have experience in Data Quality Assessments & Data Evaluations.
  • Experience in building AI/ML models will be added advantage.

Thanks & Regards

Vikarant Kumar

- provided by Dice

 
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