About the Role:
We’re seeking an up-and-coming Data Scientist with 1–4 years of experience who is eager to grow into a senior-level role over time. This position offers a unique opportunity to gain exposure across a wide variety of data science projects, including fraud detection, government analytics, and machine learning applications. You’ll work in a collaborative, mission-driven environment where your contributions will directly impact public programs and policy.
Key Responsibilities:
- Conduct contextual research using policy manuals, data dictionaries, news articles, and academic literature to inform data tasks.
- Collaborate with audit teams and external stakeholders to clarify data requirements and contextual gaps.
- Process and analyze data using Python, R, and SQL.
- Document data processing steps and prepare specification documents.
- Apply AI/ML techniques and rules-based methods to generate insights, detect anomalies, and summarize statistics.
- Develop machine learning models to identify fraud, waste, and inefficiencies in government programs.
- Create dashboards and visualizations using Tableau, PowerBI, or Matplotlib.
- Deliver professional reports and Excel workbooks detailing findings.
- Present insights in a clear, actionable format for both internal and external audiences.
- Automate data pipelines and enhance data collection methodologies.
- Stay current with emerging trends in data science and public sector analytics.
Required Qualifications:
- Bachelor’s degree in Computer Science, Information Technology, or a related field.
- 1–4 years of professional experience in data science or analytics.
- Proficiency with modern cloud-based tools (e.g., AWS, Redshift).
- Experience with Databricks.
- Strong programming skills in Python, R, or similar languages.
- Familiarity with machine learning libraries such as TensorFlow, Scikit-Learn, or PyTorch.
- Experience with data visualization tools like Tableau, PowerBI, or Matplotlib.
- Excellent communication and documentation skills.
- Ability to work independently and collaboratively in a fast-paced environment.
