Job Type: Contract (6 Months)
Experience: 6–10 Years
Work Location: Remote
Shift Timing: Start around 7:00–7:30 AM IST
Job Summary
We are seeking an experienced Senior Data Scientist to join our team and lead the development of advanced Machine Learning, Artificial Intelligence, and predictive analytics solutions. The ideal candidate will have strong expertise in building production-grade ML models, working with AWS AI/ML services, and translating complex business problems into scalable data-driven solutions.
This role requires hands-on experience with AWS SageMaker, Amazon Bedrock, Python, MLOps, and advanced statistical modeling to support enterprise-scale AI initiatives.
Key Responsibilities
- Design, develop, and deploy Machine Learning models for forecasting, demand prediction, customer churn, and behavioral analytics.
- Build scalable predictive analytics solutions using statistical modeling and machine learning techniques.
- Develop, train, evaluate, and optimize ML models for production environments.
- Collaborate with data engineers and software development teams to deploy models using AWS SageMaker Pipelines.
- Integrate and evaluate Foundation Models using Amazon Bedrock APIs.
- Perform feature engineering, data preprocessing, and model validation.
- Monitor model performance, identify drift, and implement continuous improvements.
- Build and maintain scalable MLOps pipelines and feature stores.
- Work with structured and unstructured datasets to derive actionable business insights.
- Communicate technical findings effectively to business stakeholders and leadership.
- Follow cloud security, governance, and AI best practices.
Required SkillsMachine Learning & Data Science
- 6–10 years of experience in Data Science and Machine Learning.
- Strong proficiency in Python.
- Experience with:
- Machine Learning model development and deployment
- Statistical Modeling
- Feature Engineering
- Model Monitoring and Performance Optimization
- Predictive Analytics
Domain Expertise (One or More)
- Time Series Forecasting (Prophet, ARIMA, LSTM, or similar)
- Customer Behavior Analytics
- Churn Prediction
- Survival Analysis
- Supply Chain Analytics
- Demand Forecasting
- Inventory Optimization
Mandatory AWS Skills
- AWS SageMaker (Pipelines, Model Registry, Endpoints)
- Amazon Bedrock
- Amazon S3
- AWS Glue
- Amazon Athena
- AWS Lambda
- AWS Step Functions
- Amazon Redshift
Cloud & Platform Experience
- Deploying Machine Learning solutions on AWS
- Foundation Model integration using Amazon Bedrock
- Data transformation and analytics using AWS services
- MLOps implementation and automation
- IAM Roles, VPC Configuration, and AWS Security Best Practices
Preferred Qualifications
- Experience with production-scale Machine Learning deployments.
- Experience implementing Feature Stores.
- Strong understanding of MLOps frameworks and CI/CD for ML.
- Experience delivering enterprise AI/ML solutions.
- Knowledge of Generative AI and Foundation Models.
- Experience working in Agile/Scrum environments.
Soft Skills
- Strong analytical and problem-solving abilities.
- Excellent verbal and written communication skills.
- Ability to explain technical concepts to non-technical stakeholders.
- Self-motivated and capable of working independently in a remote environment.
- Strong collaboration and stakeholder management skills.
- Passion for AI, Machine Learning, and continuous learning.
Pay: ₹100,000.00 - ₹150,000.00 per month
Experience:
- Python: 6 years (Required)
- Data science: 8 years (Required)
Work Location: Remote
