Senior Data Scientist

Job Summary:

Senior Data Scientist

Key Responsibilities:

• Lead end-to-end data science projects from problem definition to model deployment.
• Apply advanced statistical techniques (e.g., hypothesis testing, Bayesian inference, time series analysis) to solve business problems.
• Design, build, and validate machine learning models for classification, regression, clustering, and recommendation systems.
• Interpret model results and communicate findings to stakeholders with clarity and impact.
• Collaborate with data engineers to ensure scalable data pipelines and model integration.
• Mentor junior data scientists and contribute to best practices in model development and evaluation.
• Stay current with the latest research and trends in ML/AI and apply them to real-world problems.

Required Qualifications:

• Master's or Ph.D. in Statistics, Mathematics, Computer Science, or a related field.
• 3-5+ years of experience in data science, with a strong portfolio of statistical and ML projects.
• Proficiency in Python or R, and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Good Understanding in NLP, NER Techniques, RAG pipelines, Multi-Agent RAG pipelines, Hybrid search and context similarity techniques.
• Strong foundation in statistical theory and its practical applications.
• Experience with cloud platforms (Snowpark, Azure ML) and MLOps tools is a plus.
• Excellent communication and storytelling skills with data.

Preferred Skills:

• Experience in causal inference, A/B testing, and experimental design.
• Familiarity with deep learning architectures and NLP techniques.
• Exposure to big data tools like Spark, Snowflake, or Databricks.
• Domain expertise in [e.g. healthcare] is a plus.