Job Purpose:
To develop data-driven use cases and provide actionable intelligence using advanced data analytics tools and methodologies to support the organization in achieving digitization goals, strategic and tactical decision-making by acquiring, transforming, and modeling data.
The Job:
- Develop advanced analytics, ML (supervised/unsupervised), AI, and LLM-based (Generative AI) solutions as POCs and production-ready systems using relevant frameworks.
- Conduct exploratory Data Analysis, feature engineering, hypothesis testing, and other statistical techniques to identify important features for modeling.
- Present analytical findings and AI strategies to senior management in a clear, business-focused manner.
- Collaborate closely with MLOps/DevOps teams to productionize models, automate pipelines, and ensure scalability and reliability.
- Provide L3 support for AI/ML/GenAI solutions in production environments.
- Conduct research on emerging AI technologies (LLMs, multi-modal models, AI agents, etc.) and evaluate their applicability to business use cases.
- Prepare AI/analytics roadmaps aligned with business strategy.
- Define model governance frameworks including performance tracking metrics, explainability, and retraining strategies.
- Monitor outcomes and optimize models/business processes with stakeholders.
- Maintain documentation and version control.
- Collect feedback from model output to improve and optimize AI & ML model performance.
- Maintain up-to-date knowledge on new technologies/best practices.
- Groom junior data analysts/intern data scientists.
- Provide on-the-job training sessions to interns.
- Facilitate knowledge sharing and collaboration building.
The Person:
- Bachelor’s Degree in AI/Data Science/ Computer Science/Engineering/ Information Technology/ or a related field.
- 2+ years of experience in Data Science.
- Excellent understanding of machine learning techniques and algorithms.
- Proven hands-on experience with Python (mandatory) and relevant ML/AI libraries (Scikit-learn, TensorFlow, PyTorch, etc.).
- Data visualization and communication skills.
- Hands-on-experience in working with any major cloud provider (AWS, GCP, Azure)
- Good understanding of Gen AI/ Agentic AI technology stack
- Experience in data engineering in different environments (data warehouse/big data/cloud storage).
- Score 70%+ on the Data Scientist entry exam (External hires).
- AFF Data Science (Basic).
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