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Data Scientist
New York, New York
W2 - Contract
Immediate
Remote
Posted On 01/23/2026
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Android Developer
Ordinary, Virginia
W2 - Contract
1 Week
Posted On 01/26/2026
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AWS DevOps Consultant
Ordinary, Virginia
W2 - Contract
Immediate
Posted On 01/26/2026
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Java Full Stack Developer
Ordinary, Virginia
W2 - Contract
Immediate
Posted On 01/26/2026
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Python Developer
Ordinary, Virginia
W2 - Contract
Immediate
Posted On 01/26/2026
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Sr Full Stack Developer
New York, New York
W2 - Full Time
Immediate
Remote
Posted On 01/23/2026
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Full stack developer/Aws
New York, New York
W2 - Full Time
Immediate
Remote
Posted On 01/23/2026
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Cloud/SRE Engineer
New York, New York
W2 - Full Time
Immediate
Remote
Posted On 01/23/2026
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QA Test Engineer Lead
New York, New York
W2 - Full Time
Immediate
Remote
Posted On 01/23/2026
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Senior Java Full Stack Developer
Schenectady, New York
W2 - Full Time
1 Week
Posted On 01/22/2026
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Sa3 Holding Info
Schenectady, New York

MN
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Created On 01/23/2026
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Candidate ID:CID10100035

Data Scientist

Available
New York, New York, US
Pay Rate : 45 - 60 USD / month
Experience : 6 YearsAvailability : ImmediateEngagement Type: W2 - Contract
Hybrid
Security Clearance
Resume

Candidate Details
Primary Skills
Predictive Modeling
Data Analysis
Statistical Modeling
Data Wrangling
Secondary Skills
Data Mining
Feature Engineering
Data Cleaning
ETL Processes
Experience
6 Years

Candidate Summary
Data Scientist with 5+ years of total experience Primary domain expertise: Data Science - focusing on machine learning and data analytics Core technical stack: Python, SQL, Spark, Tableau, AWS Key specializations: Expertise in predictive modeling, data visualization, and statistical analysis Career focus: Known for developing robust data-driven solutions and enhancing predictive analytics Major career milestones include transitioning from Data Analyst to Data Scientist and leading significant projects in fraud detection Key projects delivered include developing intricate Spark SQL queries and enhancing fraud prediction performance using machine learning techniques