IT_Industries4.0_Data Scientist_CoE

Welspun World

Hyderabad

On-site

INR 1,200,000 - 2,000,000

Full time

14 days+

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Job summary

A leading technology company in Hyderabad is seeking an experienced Data Scientist to develop and deploy AI/ML and Generative AI solutions. The ideal candidate will have 4-5 years of expertise and a strong foundation in machine learning, deep learning, and data engineering. Responsibilities include end-to-end model development and collaborating with various teams. This role offers an opportunity to engage in innovative AI projects and mentor junior staff while staying updated with the latest industry trends.

Qualifications

4-5 years of expertise in developing and deploying AI/ML and Generative AI solutions.
Deep understanding of machine learning, deep learning, generative models, statistical modelling, and data engineering.
Experience with big-data technologies like Spark and Hadoop.

Responsibilities

Design and deploy machine learning and deep learning models for various use cases.
Develop Generative AI models such as Transformers and GANs.
Optimize data pipelines and collaborate with cross-functional teams.

Skills

AI/ML models

MLOps pipelines

Artificial Intelligence

Chatbot

Python

PySpark

SQL

Business & Commercial acumen

Entrepreneurship

Global mind-set

People excellence

LLMs

Low Traditional Modeling

GenAI

Job description

Job Purpose/ Summary

We are looking for an experienced Data Scientist with 4-5 years of expertise in developing and deploying AI/ML and Generative AI solutions. The ideal candidate will have a deep understanding of machine learning, deep learning, generative models, statistical modelling, and data engineering. They will be responsible for end-to-end model development, optimizing data pipelines, and collaborating with cross‑functional teams to drive business impact.

Job Title

IT_Industries4.0_Data Scientist_CoE

Job Description

Data Scientist with 4-5 years of expertise in developing and deploying AI/ML and Generative AI solutions. The ideal candidate will have a deep understanding of machine learning, deep learning, generative models, statistical modelling, and data engineering. They will be responsible for end-to-end model development, optimizing data pipelines, and collaborating with cross‑functional teams to drive business impact.

Principal Accountabilities

Design, develop and deploy machine learning and deep learning models for various use cases including classification, regression, time‑series forecasting, NLP and Generative AI applications.
Develop and finetune Generative AI models such as Transformers, GANs, VAEs and Diffusion Models for applications like text generation, image synthesis and conversational AI.
Utilize advanced techniques like hyperparameter tuning, feature selection, transfer learning and prompt engineering to enhance model performance.
Develop and maintain realtime and batch AI/ML pipelines in production environments ensuring efficient data processing and model deployment.
Extract, clean and transform large‑scale structured and unstructured datasets to support data‑driven decision‑making.
Work with big‑data technologies including Spark and Hadoop to handle large‑scale data processing tasks.
Deploy ML and Generative AI models using containerization technologies like Docker and Kubernetes and leverage cloud platforms such as AWS, Azure or GCP.
Implement MLOps and GenAI Ops best practices to automate model retraining, monitoring and CICD pipelines ensuring robust and scalable AI solutions.
Optimize the inference performance of large‑scale foundation models including LLMs, Vision Models and Multimodal Models for production use.
Perform exploratory data analysis (EDA) to generate actionable insights and support data‑driven strategies.
Collaborate with stakeholders to understand business challenges and provide AI‑driven solutions including GenAI‑powered automation and augmentation.
Design AB testing frameworks to validate model performance and assess business impact effectively.
Drive the adoption of LLMs, chatbots and AI copilots for various business use cases enhancing operational efficiency and customer engagement.
Mentor and guide junior data scientists and data engineers fostering a culture of continuous learning and innovation.
Collaborate with product managers, data engineers and business leaders to drive the adoption of AI/ML and Generative AI technologies across the organization.
Stay updated with the latest trends in AI, LLMs, multimodal AI and GenAI innovations contributing to research and innovation initiatives within the company.