Analyst and Consultant

2 weeks ago


India Sirius AI Full time

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.



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