We are seeking an experienced Data Scientist with strong expertise in designing, developing, and deploying data-driven ML solutions on AWS. The ideal candidate should have hands-on experience in machine learning, statistical modeling, data engineering, and data visualization, with the ability to translate business problems into analytical solutions.
Key Responsibilities
- Develop and deploy ML models and analytical solutions using AWS cloud services
- Perform EDA, data cleaning, feature engineering, and data preprocessing
- Build predictive and prescriptive models using Python (scikit-learn, TensorFlow, PyTorch)
- Collaborate with data engineers and business teams for smooth data pipelines
- Automate model training, validation, deployment using SageMaker, Lambda, Glue, Step Functions
- Evaluate model performance and optimize for accuracy and scalability
- Present insights using Tableau, Power BI, QuickSight
- Stay updated on emerging AI/ML and AWS technologies
Required Skills & Qualifications
- Bachelor's/Master's in CS, Statistics, Mathematics, Data Science, or related fields
- 58 years of experience in Data Science / ML / Advanced Analytics
- Proficiency in Python (pandas, numpy, scikit-learn, TensorFlow, PyTorch) and SQL
- Experience with AWS services: SageMaker, Glue, Lambda, Redshift, S3, Athena, EC2
- Strong understanding of statistical analysis, data modeling, preprocessing
- Experience with Git and CI/CD pipelines
- Excellent problem-solving and communication skills
Preferred Skills
- MLOps tools: MLflow, Kubeflow, SageMaker Pipelines
- Experience in NLP, time-series forecasting, or computer vision
- Visualization tools: QuickSight, Power BI, Tableau
- Containerization & orchestration: Docker, Kubernetes
Soft Skills
- Strong analytical and critical-thinking abilities
- Effective communication and presentation skills
- Ability to work independently or in cross-functional teams
- High attention to detail and strong business acumen
