Data Scientist

Wise Equation Solutions
Greensboro, NC, United States
about 2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Confluence JIRA Databases Computer Engineering Extract Transform Load (ETL) Data Masking Data Systems Data Visualization Amazon DynamoDB Python (Programming Language) Machine Learning
+25 more
Power BI DataOps Amazon Simple Notification Service (SNS) Software Engineering SQL Stored Procedures SQL Databases Systems Integration Tableau (Software) Data Processing Real Time Systems Snowflake Gitlab Data Lakes Pyspark Information Technology Wikis Dataiku Amazon Simple Queue Service (SQS) Splunk Data Pipelines Api Management Alteryx Amazon Redshift Databricks Programming Languages

Job description

  • Create scalable data pipelines using Glue, Eventbridge, DynamoDB to process life insurance data and support data modeling for policy records, claims, actuarial datasets.
  • Write and optimize ETL and reconciliation workflows using PySpark and Python to transform raw policyholder data into analytics-ready datasets for reporting and decision-making.
  • Build and implement event-driven data solutions on AWS, leveraging SQS, SNS, and API integrations to enable real-time processing of insurance transactions and policy events
  • Implement snowflake data masking and row level security policies to ensure sensitive policyholder and beneficiary data are protected.
  • Create Splunk data pipelines and PowerBI dashboards to ingest, index and analyze structured and unstructured life insurance data including policy transactions, claims events enabling real-time operational monitoring.
  • Build flow zones and manifest file generator in Dataiku to develop data processing logic that meets life insurance business and regulatory requirements
  • Write and optimize ETL workflows using data-oriented programming languages such as PySpark and Python to extract and transform raw policyholder data and support machine learning model development by preparing high-quality, analytics-ready datasets for reporting and decision-making.
  • Write SQL queries and stored procedures in Amazon redshift to support life insurance reporting, premium reconciliation, and claim analytics and implement optimized data modeling techniques for analytical workloads.
  • Develop end-to-end data workflows in Dataiku, integrating multiple sources to extract and analyze life insurance data such as policy administration systems, claims databases and actuarial feeds for business insights.
  • Write and optimize Delta Lake table implementations in Databricks to support efficient storage, ACID transactions, and time travel queries on life insurance datasets.
  • Build and maintain alteryx server scheduled workflows to automate end-to-end data processing pipelines for life insurance data and enable data visualization for claims reporting on Tableau.
  • Work on Jira tickets for the sprint plan and utilize Gitlab repositories and confluence and participate in retrospective meetings

Requirements

Do you have experience in Wiki systems?, Minimum Education Requirement:- This position requires, at a minimum of a bachelor’s degree in computer science, computer information systems, information technology, relevant engineering, (computer engineering, software engineering, electronic engineering or related) or a combination of education and experience equating to the U.S. equivalent of a Bachelor’s degree in one of the aforementioned subjects.

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