We are looking for an experienced Senior Machine Learning Engineer with 6+ years of experience in Machine Learning/Data Science and solid hands-on experience in the US Healthcare domain.

The ideal candidate should have strong expertise in Python, SQL, Machine Learning, statistical modeling, feature engineering, and model deployment, along with a good understanding of US healthcare data such as claims, member, provider, clinical, and payer data.

Key Responsibilities:

- Design, develop, and deploy end-to-end Machine Learning models for healthcare use cases.
- Work with large-scale US healthcare datasets, including claims, member, provider, clinical, and payer data.
- Perform data preprocessing, feature engineering, exploratory data analysis, model development, validation, and performance tuning.
- Develop ML models for use cases such as payment integrity, fraud/waste/abuse detection, risk prediction, cost optimization, claims analytics, and healthcare operations.
- Build scalable ML pipelines using Python and SQL.
- Apply supervised and unsupervised learning techniques such as:

- Regression

- Classification

- Clustering

- Anomaly detection

- Forecasting
- Decision trees / Random Forest

- XGBoost / LightGBM

- Neural Networks
- Deploy and operationalize ML models in production environments.
- Implement MLOps practices, including model versioning, experiment tracking, CI/CD, model monitoring, and performance tracking.
- Collaborate with Data Engineers, Data Scientists,



Business Analysts, and healthcare SMEs to understand business requirements and convert them into ML solutions.
- Analyze healthcare claims and identify meaningful patterns, trends, anomalies, and business opportunities.
- Ensure data quality, model accuracy, scalability, and reproducibility.
- Present technical findings and model outcomes to technical and non-technical stakeholders.
- Mentor junior team members and contribute to ML best practices and technical standards.

Required Skills

- 6+ years of hands-on experience in Machine Learning, Data Science, or ML Engineering.
- Strong experience with US Healthcare / Health Insurance domain.
- Strong proficiency in Python and SQL.
- Hands-on experience with scikit-learn, Pandas, NumPy and other ML libraries.
- Strong understanding of machine learning algorithms and statistical concepts.
- Experience in feature engineering, model validation, model optimization, and model deployment.
- Experience working with large datasets and healthcare data.
- Strong understanding of US healthcare claims, payer, member, provider, or clinical data.
- Good understanding of healthcare concepts such as Medicare, Medicaid, claims processing, payment integrity, FWA, ICD-10, CPT/HCPCS, provider and member data.

Location: Bangalore Work Mode: Hybrid (2 Days Work From Office in a week)

Shift Timing: 2 PM 11 PM

Regards,

[email protected]

📌 Data Scientist (Bengaluru)
🏢 Sagility India
📍 Bengaluru