Zensar Technologies

2 weeks ago

Pune, India Zensar Technologies Full time

Job Title : Analyst Data Science

Experience : 3-8 Years

About the Role :

We are seeking a skilled Data Science Analyst with hands-on experience in designing and implementing end-to-end machine learning pipelines. You will leverage advanced AI technologies including Large Language Models (LLMs) and Generative AI to drive impactful data analysis, predictive modeling, and business insights. Your expertise will be critical in deploying scalable ML solutions within cloud environments, particularly Microsoft Azure.

Key Responsibilities :

- Design, build, and maintain machine learning pipelines covering dataset curation, model training, testing, validation, and production deployment.

- Apply supervised, unsupervised, and deep learning methods to solve business challenges such as recommendation engines and scoring systems.

- Utilize LLMs and Generative AI techniques to enhance NLP and predictive capabilities.

- Conduct A/B testing and use statistical methods to assess and improve model performance.

- Collaborate effectively with cross-functional teams to embed ML solutions into business processes and systems.

- Manage model lifecycle including versioning, retraining, and deployment.

- Utilize cloud-based ML platforms and tools for model development and deployment.

Required Skills & Qualifications :

- 3-8 years of practical experience in machine learning and data science.

- Proficient in Python or R for model building, data mining, and large dataset analysis.

- Experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, and ONNX.

- Strong understanding and hands-on experience with Microsoft Azure services : Azure Machine Learning, Azure Cognitive Services, Azure Databricks.

- Experience with LLMs and Generative AI frameworks, including model fine-tuning and deployment.

- Knowledge of cloud ML platforms, preferably Azure, with experience in setting up data and experimentation environments.

- Familiarity with model management tools such as Azure ML Service and MLflow.

- Experience deploying models using Azure Kubernetes Service (AKS) or similar orchestration platforms.

- Solid foundation in statistical modeling and machine learning algorithms.

- Strong communication skills to translate technical concepts for business stakeholders.


(ref:hirist.tech)

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