We are seeking an accomplished Senior Data Science and Machine Learning Engineer to join our Healthcare Innovation and Learning System (HILS) team

Experience: 6 Years - 12 Years

Location: Bangalore

Notice Period: Immediate to 30 days

Working Model: Hybrid

Preferred but not required: Demonstrated experience within the US Healthcare Payer domain; familiarity with payer data models, claims processing, and regulatory context is strongly preferred.

Key Responsibilities

- Develop a thorough understanding of the Javelina data model and its associated ecosystem components to inform model design and data strategy.
- Design, develop, and manage ETL pipelines using DBT to transform Javelina data into structured transformation layers fit for machine learning consumption.
- Architect and maintain synthetic datasets aligned with a holistic Healthcare Payer data ecosystem for specific Javelina use cases.
- Curate, cleanse, and prepare datasets for ML model development and training, including synthetic data for supervised and reinforcement learning scenarios.
- Select appropriate algorithms and model architectures to address specific business problems within the Javelina platform and the broader healthcare payer domain.
- Establish, manage, and maintain a robust MLOps workplace to facilitate model training, versioning, deployment, and monitoring in support of Javelina.
- Design and implement automated validation and testing frameworks to ensure model correctness, completeness, and reliability.
- Expose trained models via REST APIs to support proof-of-concept development, demonstrations, and product integrations within the Javelina ecosystem.
- Define, capture, and publish metrics pertaining to model quality, performance, and usage.




- Produce comprehensive technical documentation of models for consumption by Javelina product and development teams.
- Continuously improve model performance through supervised learning techniques and iterative feedback loops.
- Identify and develop frameworks for performing supervised and reinforcement learning at scale.
- Collaborate with Javelina product development and support teams to define data requirements for building targeted models.
- Mentor and educate team members on machine learning best practices and model development methodologies.
- Evaluate emerging tools, technologies, open-source frameworks, and commercial ML models relevant to the healthcare payer industry.
- Engage with hyperscalers, startups, and strategic partners to identify models that complement and augment the Javelina product roadmap.

Required Technical Skills Data Engineering & Transformation

- DBT (Data Build Tool) advanced proficiency in transformation pipeline development
- SQL complex querying, optimization, and schema design
- PostgreSQL and MySQL relational database design and management
- Neo4j and graph databases (is a plus) graph data modeling and querying

Machine Learning & Data Science

- Python Pandas, NumPy, Scikit-Learn, PyTorch
- TensorFlow — deep learning model development and deployment
- Hugging Face — large language model integration and fine-tuning
- Amazon SageMaker — cloud-based ML training and inference pipelines

Preferred
- Linux — command-line proficiency and shell scripting
- Docker — containerization for reproducible ML environments

If you’re interested share your update resume [email protected] including below details.

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K Mohamed Althaf

Talent Acquisition Group [email protected]

📌 Delivery Module Lead - Senior Data Science and Machine Learning (Bengaluru)
🏢 Mphasis
📍 Bengaluru