Predictive Analytics Data Scientist-AI Labs
Top Gen AI Jobs
Predictive Analytics Data Scientist-AI Labs
Adani Enterprises Limited
Ahmedabad
3-5 years
Today
$24.1K–37.3K/yr
Full-time
Onsite
Skills Required
LLM
RAG
Gen AI
Machine Learning
MLOps
Predictive analytics
Time-series forecasting
Regression analysis
Anomaly detection
Feature engineering
Hyperparameter tuning
Deep Learning
Model evaluation
Bias mitigation
AWS
Description
Predictive Analytics Data Scientist role focused on building, deploying, and governing AI-driven forecasting and optimization solutions.
Role: Predictive Analytics Data Scientist-AI Labs
Location: Ahmedabad, Gujarat, India
Qualification
- Master’s degree in Computer Science
- Master’s degree in Data Science
- Master’s degree in Statistics
- Master’s degree in Mathematics
- Master’s degree in Artificial Intelligence
- Master’s degree in a related field
- Certified Machine Learning Engineer
- Google AI Certification
- AWS AI Certification
- Microsoft AI Certification
- Professional Certification in Predictive Analytics
- Coursera certification
- IBM certification
- DataCamp certification
- MLOps & Cloud AI Certification
- AWS certification
- GCP certification
- Azure certification
- Develop and train predictive models to solve business challenges
- Optimize predictive accuracy through feature engineering, hyperparameter tuning, and deep learning
- Test, refine, and validate AI models for reliability
- Ensure real-time model scalability on cloud-based AI infrastructure
- Translate business challenges into AI-driven solutions aligned with strategic objectives
- Enhance operational efficiency through predictive analytics in decision workflows, process automation, and real-time optimization
- Deploy AI models into production and integrate them into enterprise applications and business workflows
- Monitor model performance in real-world scenarios
- Continuously improve model efficiency through iterative learning and retraining
- Work closely with model deployment teams to operationalize AI solutions
- Coordinate with front-end developers to integrate predictive insights into dashboards and user applications
- Partner with business teams to align AI models with KPIs and measurable business impact
- Ensure AI compliance with regulations, data privacy laws, and governance frameworks
- Implement explainability frameworks to improve transparency and interpretability
- Conduct risk assessments to identify model bias, ethical concerns, and unintended consequences
- Implement AI-powered demand-supply forecasting for production planning, logistics, and inventory management
- Improve cost management and revenue forecasting using AI models
- Leverage AI models for risk assessment, fraud detection, and business performance monitoring
- Manage structured and unstructured data pipelines
- Conduct feature extraction and engineering to improve model performance
- Automate model training pipelines for scalability, version control, and real-time learning capabilities
- Identify and address model drift, bias, and performance degradation
- Deploy solutions in collaboration with AI vendors, research institutions, academia, and regulatory bodies
stress testing, GCP, Azure, Kubernetes, Docker, AI-powered demand-supply forecasting, risk assessment, fraud detection, business performance monitoring, structured data, unstructured data, feature extraction, model training pipelines, model deployment, model monitoring, model drift, explainability frameworks, data privacy laws, GDPR, AI Act
Other
- Key stakeholders include AI & Data Science Teams, Business Leaders & Strategy Teams, IT & Cloud Engineering Teams, and Finance & Risk Management Teams
- External stakeholders include Technology Partners & AI Vendors, Research Institutions & Academia, and Regulatory Bodies
Recommended resources to build the skills for this position. Sponsored.
Generative AI with Large Language Models
Coursera
Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.
Large Language Models: Application through Production
edX
Production-focused LLM course covering deployment, monitoring, and scaling.
Deep Learning Specialization
Coursera
Five-course deep learning series covering CNNs, RNNs, transformers, and ML strategy.
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