Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in Richmond, VA, with a contract length of "unknown" and a pay rate of "unknown." Key skills include machine learning, predictive analytics, and expertise in SQL, Python, and big data platforms. In-person interviews required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
June 11, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Reston, VA
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🧠 - Skills detailed
#Data Lake #GitHub #Oracle #Jupyter #Shell Scripting #Apache Spark #Programming #Strategy #JSON (JavaScript Object Notation) #Microsoft SQL Server #XML (eXtensible Markup Language) #Redshift #SQS (Simple Queue Service) #AWS (Amazon Web Services) #Python #Visualization #Cloud #IAM (Identity and Access Management) #SNS (Simple Notification Service) #ML (Machine Learning) #Lambda (AWS Lambda) #Spark (Apache Spark) #Data Pipeline #VPC (Virtual Private Cloud) #MySQL #Web Services #Scripting #SQL (Structured Query Language) #BI (Business Intelligence) #MS SQL (Microsoft SQL Server) #RDS (Amazon Relational Database Service) #SQL Server #Microsoft SQL #GIT #EC2 #Snowflake #Looker #AWS EC2 (Amazon Elastic Compute Cloud) #Data Science #Big Data #HDFS (Hadoop Distributed File System) #Athena #PostgreSQL #Microsoft Power BI #S3 (Amazon Simple Storage Service) #Spark SQL #Tableau Desktop #Azure #PySpark #Tableau
Role description
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Data Scientist
Richmond, VA - Onsite
In-person interview - Locals only
State of VA: 765167
Skills Specific to this Position:
Provide expertise to agency on data-driven decision making and strategy.
Provide expertise in specific areas, such as machine learning, predictive analytics using data and systems related to public procurement.
Leading research projects, for advanced date mining, developing algorithms, or building data pipelines related to public procurement.
Tools and Technologies:
Programming languages: SQL, Python, PySpark, Shell Scripting, PowerShell
Data visualization: Tableau Desktop & Server, Power BI, Looker, Jupyter Notebooks
Other frameworks: git, GitHub, SSH Secure Shell, Putty, XML, JSON, SQL Workbench
· Big data platforms: Apache Spark, Spark SQL, Hive, HDFS, MapReduce, Azure Data Lake
Cloud platforms: Amazon Web Services (AWS), EC2, S3, RDS, VPC, EMR, SNS, IAM, Redshift, CloudWatch, SQS, Route53, CloudFront, Athena, Kinesis, QuickSight, Lambda.
Statistical tools: Snowflake, Redshift, Oracle, MySQL, Microsoft SQL Server, PostgreSQL
