Data Scientist - AI/ML Analytics for Federal Projects

Energy Jobline ZR; Arlington (VA); On-site; USD 120,000 - 170,000; Full time

Job summary

The Midtown Group seeks a Data Scientist to support a federal government client by leveraging advanced data analytics, ML, and AI to tackle complex datasets and mission-critical challenges. You will build data pipelines, integrate diverse sources, and translate findings into actionable insights.

Responsibilities include developing automated data pipelines, data extraction/normalization, and crafting analytics solutions using AWS/Azure, Databricks, and Azure Data Factory.

Qualifications

• US Citizenship required
• 1+ year of experience working with AWS and/or Azure services, such as Databricks, Azure Data Factory, and Azure Data Lake.
• Experience with Azure DevOps and/or GitHub, CI/CD pipelines, and Agile methodologies.
• Experience developing and optimizing automated data pipelines and ETL/ELT processes.
• Proficiency with Python and SQL; experience with R and/or JavaScript is a plus.
• Experience working with structured and unstructured data and integrating multiple data sources.
• Knowledge of machine learning, artificial intelligence, NLP, predictive analytics, statistical analysis, or data/text mining.
• Strong analytical, problem-solving, technical writing, and communication skills.
• Ability to work independently and effectively within a collaborative team environment.
• Experience with contract, procurement, and accounts payable (AP) data to identify trends, anomalies, and potential risks.
• Experience using PySpark/PySpark SQL for large-scale data processing.
• Experience with data lakes, data lakehouses, relational databases, and business intelligence tools.
• Experience supporting federal audit, investigation, oversight, fraud, waste, or abuse-related activities.
• Experience developing predictive models, NLP solutions, dashboards, and investigative or analytical visualizations.
• Experience presenting technical findings, training materials, or conference presentations to large audiences.

Responsibilities

• Develop, manage, and optimize automated data pipelines to support reliable analytics and data quality.
• Extract, clean, transform, normalize, and validate structured and unstructured data.
• Integrate data from flat files, relational databases, APIs, external systems, and other sources using JDBC/ODBC, REST APIs, and web scraping.
• Develop data and analytics solutions using AWS and/or Azure, including Databricks, Azure Data Factory, and Azure Data Lake.
• Use Azure DevOps and/or GitHub to support source control, CI/CD pipelines, and Agile development.
• Apply Python, SQL, R, and/or JavaScript to develop datasets, models, dashboards, visualizations, and reports.
• Apply advanced analytics including machine learning, AI, NLP, predictive analytics, statistical modeling, and data/text mining.
• Develop, train, evaluate, deploy, and maintain machine learning and AI models.
• Use PySpark/PySpark SQL to process and analyze large-scale datasets.
• Identify trends, anomalies, patterns, and risks to support audit, investigative, oversight, and fraud, waste, and abuse activities.
• Translate technical findings into clear narratives, recommendations, visualizations, and presentations.
• Develop technical documentation, requirements, test plans, methodologies, and training materials.
• Collaborate with technical teams, stakeholders, and management and provide guidance on data access, quality, storage, and analytics.

Skills

Python & SQL

Data analytics

Machine learning

ETL/ELT pipelines

AWS & Azure

Data integration

Data visualization

Technical writing

Independent work

Tools

Databricks

Azure Data Factory

Azure Data Lake

Azure DevOps

GitHub

JDBC/ODBC

REST APIs

PySpark

Job description

The Midtown Group seeks a Data Scientist to support a federal government client by leveraging advanced data analytics, ML, and AI to tackle complex datasets and mission-critical challenges. You will build data pipelines, integrate diverse sources, and translate findings into actionable insights.

Responsibilities include developing automated data pipelines, data extraction/normalization, and crafting analytics solutions using AWS/Azure, Databricks, and Azure Data Factory.