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Data Engineer with R / python language experience - Tampa FL contract

Xoriant Corporation

Location: Tampa, FL 33601
Type: Temporary (unspecified), Temporary (long-term), Non-Remote
Posted on: September 8, 2020
This job is no longer available from the source.
Data science, Data analysis, Python, R, Data engineering, Data manipulation, data engineer
Contract W2, 7 Months
Depends on Experience
Hi
Hope you are doing well.
This is Satyajit Roy from Xoriant Solutions. One of our direct clients looking to hire a Data Engineer with R / python language exp. If interested, please revert with your updated resume.
Title: Data Engineer with R / python language exp
Location: Tampa FL (remote for now)
Duration: 7+ months Contract
Key points:
• Need Advanced Excel Skills,
• Someone who can do coding on R language, Data analysis, Data manipulation, Use R to manipulate and update data.
• Migrate data, manually update and consolidate data on excel for generating code
• Streamline process, Good Data Analytical / Data science Skills,
• Financial domain exp. is desired
The candidate leverages modern data analytics languages (such as R and Python) to quickly and efficiently manipulate large datasets and better aid in analysis. Use data science skills R and Python to create efficiencies in the Risk Weighted Assets (RWA) analysis process by:
• Combining large data sets to automate period of period analysis
• Automate the identification of period over period variance drivers
• Create automation of the attribution of variance analysis of attributes identified by the SMEs
• Automate the output into templates required by upstream teams
• Effectively document code created to ensure the process is repeatable
Success will be defined by a successful usage of R and Python to more quickly consume various datasets and generate variance findings. The candidate must be able to articulate the process and guide the SMEs through the underlying results to ensure their clarity in the results and that a clear story for executive consumption can be articulated.