Senior Data Scientist (AWS ML & GenAI) – Remote Contract
Job Title: Senior Data Scientist
Experience: 6–10 Years
Work Mode: Remote
Contract Duration: 6 Months
Shift Timing: Early Shift (Start around 7:00–7:30 AM IST)
Employment Type: Contract
Job Overview
We are seeking an experienced Senior Data Scientist to join our team on a 6-month contract engagement. The ideal candidate will have strong expertise in Machine Learning, Forecasting, Predictive Analytics, AWS SageMaker, and Amazon Bedrock, with the ability to build scalable AI/ML solutions that drive business outcomes.
You will work closely with cross-functional teams to design, develop, deploy, and optimize machine learning models for forecasting, customer analytics, demand prediction, and advanced business intelligence use cases. This role requires hands-on experience in AWS cloud-based ML ecosystems and a strong understanding of MLOps best practices.
Key Responsibilities
- Design, develop, and deploy machine learning models for:
- Demand forecasting
- Customer churn prediction
- Customer behavior analytics
- Predictive and prescriptive analytics
- Build custom data science and analytics solutions aligned with business requirements.
- Collaborate with Data Engineering and Platform teams to productionize ML models using AWS SageMaker Pipelines.
- Leverage Amazon Bedrock to evaluate, integrate, and operationalize foundation models and GenAI capabilities within analytics workflows.
- Develop scalable ML pipelines, feature engineering frameworks, and model monitoring solutions.
- Translate complex analytical findings into actionable business insights for technical and non-technical stakeholders.
- Continuously monitor, validate, retrain, and optimize models to improve performance and business impact.
- Contribute to MLOps processes, feature stores, model governance, and deployment automation.
- Ensure security, scalability, and reliability of ML workloads within AWS environments.
Required Technical SkillsMachine Learning & Data Science
- Strong expertise in Machine Learning, Statistical Modeling, and Predictive Analytics.
- Experience building production-grade ML models.
- Proficiency in Python and data science libraries such as:
- Pandas
- NumPy
- Scikit-learn
- TensorFlow / PyTorch
- Experience with model evaluation, feature engineering, and hyperparameter tuning.
Domain Expertise (At Least One Required)Time Series Forecasting
- Prophet
- ARIMA / SARIMA
- LSTM
- Advanced forecasting techniques
Customer Analytics
- Churn prediction
- Retention modeling
- Survival analysis
- Customer lifetime value modeling
Supply Chain & Demand Forecasting
- Inventory optimization
- Demand planning
- Forecasting at scale
- Supply chain analytics
AWS & Cloud Requirements (Mandatory)AWS SageMaker
- Build, train, deploy, and manage ML models.
- Experience with:
- SageMaker Pipelines
- Model Registry
- Endpoints
- Feature Store
- Automated ML workflows
Amazon Bedrock
- Experience evaluating, integrating, and deploying foundation models.
- Working knowledge of Bedrock APIs and GenAI-based solutions.
AWS Data Services
- Amazon S3
- AWS Glue
- Amazon Athena
- Amazon Redshift
Serverless & Workflow Services
- AWS Lambda
- AWS Step Functions
Cloud Security & Infrastructure
- IAM Roles and Policies
- VPC Configuration
- Security best practices for ML workloads
- Scalable cloud architecture design
Preferred Qualifications
- Experience with MLOps tools and model lifecycle management.
- Exposure to Generative AI and Large Language Models (LLMs).
- Experience deploying enterprise-scale machine learning solutions.
- Strong communication and stakeholder management skills.
- Ability to work independently in a fast-paced remote environment.
What We're Looking For
- 6–10 years of professional experience in Data Science and Machine Learning.
- Proven experience delivering production-ready ML solutions on AWS.
- Strong problem-solving and analytical thinking skills.
- Hands-on expertise in forecasting, predictive analytics, or customer intelligence use cases.
- Ability to bridge business requirements and technical implementation effectively.
Pay: ₹80,000.00 - ₹110,000.00 per month
Experience:
- Senior Data Scientist (AWS ML & GenAI): 6 years (Required)
Work Location: Remote
