Analyst and Consultant - Data Science (Immediate Joiners)

Key Responsibilities

• Engage with clients to understand their business objectives and challenges, providing data-driven recommendations and AI/ML solutions that enhance decision-making and deliver tangible value.
• Solve business problems using data analysis and machine learning techniques: Conduct exploratory data analysis, feature engineering, and model development to uncover insights and predict outcomes.
• Develop and deploy AI/ML models, including supervised and unsupervised learning algorithms, NLP solutions, and model performance optimization.
• Design and implement scalable, cloud-native ML pipelines and APIs using tools like Python, Scikit-learn, TensorFlow, and PyTorch.
• Contribute to the development of AI-based applications, including but not limited to LLM use cases, while ensuring integration with broader ML system architecture.
• Collaborate with cross-functional teams to deliver robust and reliable solutions in cloud environments such as AWS, Azure, or GCP.
• Be a master storyteller for our services and solutions to our clients at various stages of engagement such as pre-sales, sales, and delivery using data-driven insights.
• Translate business problems into AI/ML project plans and provide strategic input on solutioning and model deployment strategies.
• Stay current with developments in AI, ML modelling, and data engineering best practices, and integrate them into project work.
• Mentor junior team members, provide guidance on modelling practices, and contribute to an environment of continuous learning and improvement.

Job Requirements

• 0 to 2 years of relevant experience in building AI/ML solutions, with a strong foundation in machine learning modelling and deployment.
• Experience in developing traditional ML models (e.g., regression, classification, clustering) across business functions such as risk, marketing, customer segmentation, and forecasting.
• Bachelor’s or Master’s degree from a Tier 1 technical institute.
• Proficiency in Python and experience with AI/ML libraries such as Scikit-learn, TensorFlow, PyTorch.
• Experience in end-to-end model development lifecycle: data preparation, feature engineering, model selection, validation, deployment, and monitoring.
• Experience working with unstructured data including complex PDF extraction and information retrieval pipelines.
• Familiarity with Agentic frameworks and MCP
• Strong problem-solving capabilities and the ability to independently lead tasks or contribute within a team setting.
• Effective communication and presentation skills for internal and client-facing interactions.
• Ability to bridge technical solutions with business impact and drive value through data science initiatives.