Data Science Intern

3 weeks ago

Austin, United States Texas Department of Aging & Disability Services Full time
Job Description:
The Fraud Analytics unit within the Data Reviews Division of the Office of Inspector General (OIG) is responsible for performing innovative and advanced data analytics to detect fraud, waste and abuse (FWA) in state health and human services programs such as Medicaid, the Children’s Health Insurance Program (CHIP), Supplemental Nutrition Assistance Program (SNAP) and Temporary Assistance for Needy Families (TANF) by supporting data-driven investigations, reviews, audits, and inspections.

Fraud Analytics seeks motivated and talented Data Science Interns (Data Analyst I) to contribute to the unit’s efforts with developing and implementing algorithms, artificial intelligence/machine learning (AI/ML) models, and predictive analytics in order to generate insights and actionable leads to detect and address FWA risks. This internship offers a valuable opportunity to work on real-world problems using AI/ML techniques and to contribute to the OIG’s vision of promoting the health and safety of Texans by protecting the integrity of state health and human services delivery. This position will report to the Deputy Inspector General of Fraud Analytics and will work closely with Fraud Analytics data scientists and analysts.

The Data Science Interns will gain valuable experience with complex healthcare data and will explore large-language models (LLMs) and retrieval augmentation generation (RAG). The Data Science Interns will be responsible for performing advanced level programming to clean, prepare, and query large, complex health and human services related datasets and to research and develop algorithms and models that identify data trends, patterns, and anomalies. The Data Science Interns will gain experience writing model documentation and methodology documents; communicating data science findings through data visualizations and presentations; and testing and evaluating new tools, methods, and techniques.

*** This position can telework % from any OIG location within Texas consistent with HHS telework policies. ***
Essential Job Functions:
Attends work on a regular and predictable schedule in accordance with agency leave policy and performs duties as assigned:

1. Researches, designs, implements, and deploys production AI/ML models and predictive analytics to identify risk and detect potential FWA in state health and human services programs, with a primary focus on Medicaid. Plans and conducts data analytics on large, complex datasets, using Python and SQL. Interprets and explains identified data trends, patterns, and anomalies. Develops, implements, and assesses the validity of existing and emerging AI/ML, analytical and statistical tools, methods, and techniques. Applies advanced analytical and statistical methods and techniques to known and new data sources. (50%)

2. Effectively communicates data analytics findings and related recommendations to technical and non-technical stakeholders both verbally and in writing, including written model documentation, methodology documents and detailed reporting of findings through data packages, data visualizations, and presentations. (30%)

3. Engages in collaboration and communication across internal OIG units and with external entities, including but not limited to: OIG program area customers, the OIG executive team, contractors/vendors, and team members. (20%)
Knowledge Skills Abilities:
1. Knowledge of AI/ML (including supervised and unsupervised learning techniques), analytical, and statistical tools, methods, and techniques; of data models and querying relational databases; of data wrangling, data mining and data visualization techniques; and of record keeping, including security procedures for handling, protecting, and distributing confidential data.

2. Strong programming skill in Python and using open-source data science frameworks. Experience in using SQL to query databases. Skill in Excel and PowerPoint.

3. Skill in cleaning, preparing, querying, and analyzing large, complex datasets to discover trends and patterns and deliver meaningful insights.

4. Strong analytical and problem-solving skills.

5. Ability to partner with stakeholders to translate and decompose program integrity or other agency problems into data science solutions.

6. Ability to research, learn, and apply knowledge of existing and emerging data science principles, theories, and techniques.

7. Ability to effectively summarize and communicate complex data findings and analytical methodologies in a way that is easily understandable to diverse audiences both verbally and in writing.

8. Ability to work independently as well as collaboratively.

9. Ability to prioritize tasks and manage multiple projects/assignments with competing deadlines.

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