Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. The Lead Data Scientist will drive advanced analytics initiatives focused on improving forecasting model accuracy and developing Generative AI solutions for explainability.
Responsibilities:
- Lead the design, development, and enhancement of forecasting models to improve prediction accuracy and business outcomes
- Build and deploy advanced Deep Learning models for large-scale structured and unstructured datasets
- Develop Generative AI / Explainable AI solutions to provide transparent and interpretable insights from predictive models
- Analyze healthcare datasets including claims, patient, provider, operational, or clinical data
- Collaborate with business stakeholders, product teams, and engineering teams to translate business challenges into scalable AI solutions
- Monitor model performance, retrain models, and optimize algorithms for production environments
- Mentor junior data scientists and provide technical leadership across the project
- Ensure compliance with healthcare data privacy and governance standards
Requirements:
- 8-10 years of experience in Data Science / Machine Learning roles
- Strong hands-on expertise in Forecasting models (time series, demand forecasting, predictive analytics)
- Experience with Deep Learning frameworks such as TensorFlow, PyTorch, or Keras
- Proven experience building Generative AI / Explainability models using LLMs, SHAP, LIME, or similar frameworks
- Mandatory experience working in the Healthcare domain
- Strong programming skills in Python, SQL, and ML libraries
- Excellent stakeholder communication and leadership skills
- Experience with cloud platforms such as AWS, Azure, or GCP preferred