About the Role

Key Responsibilities

• Independently design and implement end-to-end data science solutions to address business challenges.
• Develop, train, validate, and deploy machine learning models using Python and SQL.
• Perform feature engineering, model evaluation, and optimization using advanced statistical techniques.
• Build NLP solutions leveraging text, transcription, and unstructured datasets.
• Develop and integrate Generative AI and LLM-based solutions to enhance product capabilities.
• Translate business requirements into analytical frameworks and scalable ML pipelines.
• Collaborate with engineering and product teams to support model deployment and productionization.
• Identify workflow/process gaps and architect data-driven solutions for operational improvements.
• Stay updated with advancements in AI, NLP, and LLMs; evaluate emerging algorithms for business applications.
• Create documentation and present insights to stakeholders to ensure alignment with organizational objectives.

Required Qualifications

• 4–9 years of experience as a Data Scientist or in a related role.
• Strong problem-solving skills with a structured approach to complex business challenges.
• Proficiency in Python (NumPy, Pandas, Scikit-learn, etc.) and SQL.
• Hands-on experience in model development, validation, and deployment.
• Expertise in NLP techniques (text classification, entity recognition, embeddings, summarization, etc.).
• Experience working with Generative AI, LLMs, or transformer-based architectures.
• Experience handling large datasets and writing production-grade code.
• Strong communication skills with experience working with cross-functional stakeholders.

Preferred Qualifications

• Experience with model deployment frameworks (MLflow, Docker, APIs, etc.).
• Exposure to cloud platforms (AWS, Azure, or GCP).
• Experience with RAG architectures or prompt engineering.
• Familiarity with CI/CD practices for ML models.