The role focuses on implementing data science solutions and best practices while managing their lifecycle within a business unit. It involves translating business needs into technical solutions, ensuring data quality, and optimizing analytical workflows to drive innovation and efficiency
Principal Accountabilities
Advanced Data Science & AI Implementation
Develop and apply cutting-edge machine learning techniques such as ANN, XGBoost, and deep learning models to solve complex business problems.
Ensure the use of state-of-the-art AI frameworks and methodologies to enhance model accuracy, efficiency, and scalability.
Optimize AI models by fine-tuning hyperparameters, feature engineering, and advanced algorithm selection to maximize performance.
End-to-End Solution Development
Oversee the full AI project lifecycle, from data preparation and model development to deployment and monitoring.
Ensure smooth integration of AI solutions into production settings,
collaborating with engineering teams for scalable deployments.
Use project management tools like JIRA to track tasks, deadlines, and progress, ensuring structured execution of AI initiatives.
Maintain a structured framework for model versioning, documentation, and reproducibility to ensure long-term sustainability.
Experimentation & Continuous Improvement
Implement a systematic experimentation approach to identify gaps in current AI models and refine them iteratively.
Conduct A/B testing, error analysis, and post-deployment monitoring to assess model effectiveness and business impact.
Drive an innovation-first mindset, experimenting with current algorithms and methodologies to improve existing solutions.
Establish a feedback loop between model performance and business outcomes, ensuring AI-driven insights remain relevant and impactful.
Technical Leadership & Best Practices
Enforce best practices in coding, model documen
📌 Data Scientist Bengaluru (India)
🏢 Aditya Birla Management Corporation (ABMCPL)
📍 India
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