"Alerted.org

Job Description

This role supports the Medicaid Enrollment and Member domain, where accurate and timely data processing is critical. The team manages complex workflows involving HIPAA files received from state agencies, which are loaded into the member book of records. These files often require rapid correction due to downstream impacts—such as mass member terminations affecting insurance card validity.

A key component of this role involves maintaining and improving an existing anomaly detection system. Anomaly detection is a technique used in data analysis and machine learning to identify patterns or events that deviate significantly from the norm. These "anomalies" or "outliers" can indicate critical issues such as fraud, system failures, data errors, or unexpected behavior.

In the Medicaid context, anomaly detection helps flag irregularities in member data—like when a state mistakenly sends a file that terminates 25,000 members in a single day. Detecting such anomalies early can prevent downstream impacts, such as invalid insurance cards or disrupted services.

Key concepts include:

• Normal vs. Abnormal Behavior: The system learns what typical data looks like and flags anything that doesn’t fit.

• False Positives: Sometimes the system flags something as abnormal when it’s actually fine—this is a common challenge.

• Feedback Loops: These are used to improve the model by learning from past mistakes (e.g., reducing false positives).

• Machine Learning Models: Algorithms like isolation forests, autoencoders, or statistical models are often used to detect anomalies.

You will take ownership of the anomaly detection solution built by the enterprise team, evaluate its performance, and determine whether to enhance or rebuild it. The role also includes integrating this solution into the production environment and ensuring it aligns with the team’s operational goals.

Primary Responsibilities

• Take over and assess the existing enterprise-built anomaly detection solution; determine whether to fix or rebuild based on performance and accuracy.

• Design and deliver complex application systems that support strategic objectives in Medicaid enrollment.

• Collaborate with cross-functional teams to align development efforts with business goals.

• Manage knowledge transfer (KT) from the enterprise team and ensure continuity of operations.

• Develop and deploy AI/ML models using Python, with a focus on anomaly detection and backend processing.

• Work with on-prem SQL and be open to Python frameworks for data processing and modeling.

• Understand .NET architecture (no coding required) to interface with existing applications.

• Handle real-time data ingestion and transformation pipelines, especially around Medicaid 834 files.

• Communicate technical concepts to non-technical stakeholders and support decision-making with data insights.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• 5–7 years of experience in:

• Collecting, processing, and analyzing large datasets using Python programming language on Azure and GCP platforms

• Building and deploying AI/ML models using popular Python frameworks and tools on Azure and GCP cloud services

• Applying statistical analysis and data mining techniques to extract insights from data

• working with big data technologies on Azure and GCP for data processing and analysis

• Utilizing cloud services on Azure and GCP for data storage, computation, and deployment of AI/ML solutions

• Implementing data pipelines and automation processes for data ingestion and transformation on Azure and GCP"

• Collaborating with business stakeholders to understand their requirements and translate them into AI/ML-driven solutions

• Communicating complex technical concepts related to AI/ML to non-technical audiences o .NET, ASP.NET, WCF services, Angular (for integration purposes)