Data Scientist
The Midtown Group
We are seeking a Data Scientist to support a federal government client by applying advanced data analytics, machine learning, and artificial intelligence to complex datasets and mission-critical challenges. The Data Scientist will develop data pipelines, integrate diverse data sources, build analytical models, and translate complex findings into actionable insights.
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.
- 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.
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