Predictive Analytics Data Scientist-ai Labs

Job Category Technical Project Program Management About Business Adani Group Adani Group is a diversified organisation in India comprising 10 publicly traded companies It has created a world-class logistics and utility infrastructure portfolio that has a pan-India presence Adani Group is headquartered in Ahmedabad in the state of Gujarat India Over the years Adani Group has positioned itself to be the market leader in its logistics and energy businesses focusing on large-scale infrastructure development in India with O M practices benchmarked to global standards With four IG-rated businesses it is the only Infrastructure Investment Grade issuer in India Job Purpose The Predictive Analytics Data Scientist is responsible for designing building and optimizing AI-driven predictive models that enhance business intelligence risk management and operational efficiency This role will focus on end-to-end execution from data collection and model development to deployment and monitoring ensuring AI models drive actionable insights for demand forecasting process automation and business optimization Responsibilities This Role Is Explicitly for 2025-26 Pass out MTech Candidates Only Predictive Analytics Data Scientist-AI Labs Predictive Model Development Optimization Develop and train predictive models using time-series forecasting regression analysis and anomaly detection to solve business challenges Optimize predictive accuracy by implementing feature engineering hyperparameter tuning and deep learning techniques Test refine and validate AI models through rigorous model evaluation stress testing and bias mitigation to ensure reliability Ensure real-time model scalability by deploying on cloud-based AI infrastructure AWS GCP Azure using Kubernetes Docker and MLOps frameworks Business Problem Solving AI Integration Understand and translate business challenges into AI-driven solutions ensuring alignment with strategic objectives Implement AI-powered demand-supply forecasting models to enhance production planning logistics and inventory management Enhance operational efficiency by integrating predictive analytics into decision workflows process automation and real-time optimization Improve cost management and revenue forecasting by leveraging AI models for risk assessment fraud detection and business performance monitoring Data Collection Feature Engineering Model Training Manage structured and unstructured data pipelines ensuring high-quality inputs for predictive modeling Conduct feature extraction and engineering to optimize data representation and improve model performance Automate model training pipelines to enhance scalability version control and real-time learning capabilities Model Deployment Monitoring Performance Evaluation Deploy AI models into production ensuring seamless integration into enterprise applications and business workflows Monitor model performance in real-world scenarios identifying and addressing model drift bias and performance degradation Continuously improve model efficiency through iterative learning retraining cycles and adaptive optimization techniques Collaboration with AI Engineering Business Teams Work closely with model deployment teams to ensure AI solutions are effectively operationalized Coordinate with front-end developers to integrate predictive insights into AI-powered dashboards and user applications Partner with business teams to align AI models with key performance indicators KPIs and measurable business impact AI Governance Compliance Risk Management Ensure AI compliance with industry regulations data privacy laws GDPR AI Act and company-wide governance frameworks Implement explainability frameworks to improve transparency and interpretability of predictive models Conduct risk assessments to identify and mitigate model bias ethical concerns and unintended consequences Key Stakeholders - Internal AI Data Science Teams Business Leaders Strategy Teams IT Cloud Engineering Teams Finance Risk Management Teams Key Stakeholders - External Technology Partners AI Vendors Research Institutions Academia Regulatory Bodies Qualifications Educational Qualification Master s degree in Computer Science Data Science Statistics Mathematics Artificial Intelligence or related fields Certification Certified Machine Learning Engineer Google AWS Microsoft AI Certification Professional Certification in Predictive Analytics Coursera IBM DataCamp MLOps Cloud AI Certification AWS GCP Azure