Senior Data Scientist

Location: Mumbai

Experience: 711 Years

Function: Data Science & Analysis - Data Science / Machine Learning

Key Responsibilities:

Advanced Data Science & AI Development:

- Design, develop, and deploy machine learning and AI solutions for Health Insurance use cases.

- Build predictive models using techniques such as XGBoost, Artificial Neural Networks (ANN), and Deep Learning.

- Work on business-critical use cases including claims prediction, fraud detection, underwriting, pricing, and risk modeling.

- Improve model performance through feature engineering, hyperparameter tuning, and algorithm optimization.

End-to-End Model Lifecycle Management:

- Manage the complete machine learning lifecycle, including data extraction, preprocessing, model development, validation, deployment, and monitoring.

- Collaborate with engineering teams to ensure production-grade deployment of AI/ML models.

- Maintain model documentation, version control, and reproducibility standards.

Experimentation & Continuous Improvement:

- Conduct A/B testing, statistical analysis, and post-deployment performance monitoring.

- Identify model improvement opportunities and optimize solutions based on business outcomes and feedback.

- Evaluate and adopt emerging AI/ML techniques and methodologies to drive innovation.

Business & Stakeholder Collaboration:

- Partner with Health Insurance business stakeholders to understand requirements and translate them into scalable analytical solutions.

- Align AI/ML initiatives with key business objectives, including claims accuracy, fraud reduction, risk assessment, and operational efficiency.

- Present insights, recommendations, and model outcomes to both technical and non-technical stakeholders.

Technical Leadership & Best Practices:

- Establish and promote best practices for coding, model development, deployment, and documentation.

- Mentor junior data scientists and contribute to capability building within the team.

- Stay current with emerging trends and advancements in AI, machine learning, and data science.

Scalable AI Solutions:

- Develop reusable machine learning pipelines and scalable frameworks for multiple health insurance use cases.

- Ensure AI solutions are production-ready, maintainable, and scalable across business functions.

- Drive standardization, knowledge sharing, and continuous improvement across teams.

Required Skills & Qualifications:

- 711 years of experience in Data Science, Machine Learning, or related fields.

- Strong experience in the Health Insurance domain (Mandatory).

- Expertise in machine learning algorithms such as XGBoost, Random Forest, Neural Networks, and Deep Learning models.

- Strong understanding of claims analytics, underwriting, fraud detection, pricing, and risk modeling.

- Hands-on experience with Python, SQL, and machine learning libraries such as Scikit-learn, TensorFlow, and/or PyTorch.

- Experience with end-to-end model deployment and MLOps practices.

- Experience working with large-scale structured and unstructured datasets.

- Strong analytical, problem-solving, and statistical modeling skills.

- Excellent communication and stakeholder management abilities.

Technical Skills:

- Python

- SQL

- Machine Learning

- Scikit-learn

- TensorFlow

- PyTorch

- XGBoost

- NLP

- AWS

- Microsoft Azure

- Google Cloud Platform (GCP)