As a Data Science Practitioner, you will be instrumental in designing and delivering AI/ML-based decision-making frameworks and models that drive significant business outcomes. Your role will involve measuring and justifying the value of these AI/ML solutions, ensuring they align with strategic objectives and deliver tangible results.

This position requires a proactive and self-sufficient individual who can independently formulate, design, and implement advanced analytical models. You will collaborate with cross-functional teams to gather requirements and translate them into effective technical solutions. A key aspect of this role is the continuous monitoring and optimization of deployed models to ensure their accuracy and reliability, contributing to the overall success of data-driven initiatives.

- Develop and implement AI/ML-based decision-making frameworks and models for business outcomes. - Measure and justify the value of AI/ML-based solutions. - Perform independently and act as a Subject Matter Expert (SME). - Actively participate and contribute to team discussions and problem-solving. - Collaborate with cross-functional teams to gather requirements and translate them into technical solutions. - Continuously monitor and improve the performance of deployed models. - Document methodologies, processes, and results for knowledge sharing. - Support junior team members by providing guidance and sharing best practices.

- Minimum 3 years of experience in Data Science is required. - Proficiency in Data Science and strong knowledge of machine learning algorithms and their practical applications. - Experience with data preprocessing, feature engineering, and model evaluation techniques. - Ability to work with large datasets and perform data analysis to extract actionable insights. - Familiarity with programming languages commonly used in data science such as Python or R. - Understanding of statistical concepts and their application in predictive modeling. - 15 years of full-time education is required. - Experience in Deep Learning and potentially LLMs is advantageous. - Familiarity with Azure, Databricks, Power BI, and PySpark is a plus. - Must be proactive and self-sufficient.