Job Description
Job Description
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.
Qualifications
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.
Preferred
- 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.
The Midtown Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are a small, woman-owned business certified by the Women’s Business Enterprise National Council (WBENC). Operating from our headquarters in Washington, DC, we provide trusted staffing services nationwide. Our clients include thousands of the most prestigious Fortune 500 companies, law firms, financial organizations, tech innovators, non-profits, and lobbying firms, as well as federal, state and local government agencies.
\nCompany Description
The office is a collaborative working culture, with areas of professional growth!
Company Description
The office is a collaborative working culture, with areas of professional growth!