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Job Description

Description :


Key Responsibilities :


Data Analysis & Machine Learning :


- Analyze large-scale datasets to uncover actionable insights.


- Develop and deploy predictive and generative models using machine learning and GenAI techniques.


- Design and evaluate experiments to assess the impact of product and process changes.


- Collaborate with engineering teams to integrate AI/ML solutions into scalable cloud based applications.


Generative AI & Cloud Integration :


- Build and fine-tune GenAI models (e.g., LLMs, diffusion models) for business use cases.


- Leverage AWS services such as Bedrock, Lambda, and S3 etc. for model training, deployment, and monitoring.


- Implement secure and efficient data pipelines using AWS Glue, Redshift, and Athena.


Visualization & Communication :


- Create compelling dashboards and visualizations using tools like Power BI, or Tableau.


- Translate complex data insights into clear, actionable recommendations for stakeholders.


Collaboration & Mentorship :


- Work cross-functionally with product, engineering, and business teams to ensure successful AI solution delivery.


- Mentor junior analysts and data scientists on best practices in GenAI and cloud-based analytics.


Continuous Innovation :


- Stay updated with the latest trends in GenAI, AWS services, and data science.


- Continuously monitor and optimize model performance in production environments.


- Contribute to the development of internal AI/ML frameworks and reusable components.


Education :


- Bachelors or Masters degree in Computer Science, Data Science, AI


- Hands-on experience with GenAI frameworks (e.g., Hugging Face Transformers, LangChain, OpenAI APIs).


- Proficiency in AWS cloud services for data and AI workloads.


Technical Skills :


- Strong programming skills in Python; familiarity with libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.


- Experience with RESTful APIs, DevOps practices, and CI/CD pipelines.


- Knowledge of containerization (Docker, Kubernetes) is a plus.


Soft Skills:


- Excellent communication, problem-solving, and analytical thinking.


- Ability to work independently and collaboratively in a fast-paced environment.


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