Data Scientist

About Us:

Data Scientist

Key Responsibilities:

• Analyze structured and unstructured regulatory and healthcare datasets to derive insights, patterns, and predictive models.
• Design, develop, and validate machine learning models for use cases such as classification, document processing, recommendation systems, and effort estimation.
• Work with NLP techniques to extract and normalize information from regulatory texts, product labels, and public databases.
• Develop data pipelines and workflows to clean, transform, and prepare datasets for analysis and modeling.
• Collaborate with cross-functional teams including software developers, regulatory experts, and product managers to implement data science solutions in real-world applications.
• Monitor model performance, conduct error analysis, and continuously improve algorithm accuracy and efficiency.
• Contribute to research, publications, or internal white papers around regulatory data science and analytics.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or related fields.
• 2–5 years of hands-on experience in data science or applied machine learning.
• Proficiency in Python and libraries such as pandas, scikit-learn, NumPy, TensorFlow, or PyTorch.
• Strong understanding of supervised and unsupervised learning, NLP techniques, and model evaluation metrics.
• Experience working with healthcare, life sciences, or regulatory datasets is a strong plus.
• Familiarity with data cleaning, feature engineering, and data visualization tools (e.g., matplotlib, seaborn, Power BI).
• Comfortable working in an agile, fast-paced environment with evolving data challenges.

Preferred Attributes:

• Experience with large language models (LLMs), transformers, and foundation model fine-tuning.
• Background in text classification, named entity recognition (NER), or OCR-based document processing.
• Exposure to cloud platforms (AWS, GCP, or Azure) and MLOps practices is desirable.
• Curious, self-driven, and eager to explore new algorithms and technologies.