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Data Analyst
Job in
New York City, Richmond County, New York, USA
Listed on 2026-08-18
Listing for:
Georgia IT, Inc.
Full Time
position Listed on 2026-08-18
Job specializations:
-
IT/Tech
Data Analyst, Data Engineering
Job Description & How to Apply Below
Data Analyst
Location:
NY / GA – Hybrid (F2F interview is required)
Employment Type:
Contract
US Citizen, Green Card, TN, GC EAD and H4 EAD only. No third-party agencies corp to corp.
Data Role - Python, Pyspark, C++, Snowflake, Data Bricks, SDLC
Position
Description:
Implement mortgage risk models, written by Client Strats in Python, into C++. Supporting model run in various environments (ie: QA, UAT and PROD). Work with WM Strats to fully understand the models, and develop GUI around the models. Familiarity with risk modeling and simulation modeling.
Required Skills:
- 7+ years of C++ development experience
- Strong Python experience (Python, PySpark)
- Strong database experience (SQL, Databricks and Snowflake)
- Grid computing technologies
- Technical background in integration, development, and/or infrastructure
- Familiar with system architecture to understand how data flows from upstream systems to downstream integration
- Excellent relationship management, communication, teamwork, and influence skills; ability to operate at senior levels in both written and verbal communications interacting professionally with a diverse group, executives, managers, and subject matter experts
- Excellent communication, organization, facilitation and analytical skills, attention to details and ability to multi task
- Exposure to overall SDLC process, technology frameworks and tools (ex: Jira, Client Quality Center, etc.). Highly versed in various development methodologies, including waterfall and agile software development lifecycle
- Self-motivated and can work independently as well as in a team environment
- Ability to effectively prioritize and execute tasks in a high-pressure environment is crucial
Skills Desired:
- Previous experience in the financial services field, with emphasis on Market Risk area
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