Roles-

<ul>
<li>Build and deploy production-grade ML pipelines for varied use cases across operations, manufacturing, supply chain, and more</li>
</ul>

<ul>
<li>Manage analytics strategy across multiple use cases</li>
</ul>

<ul>
<li>Work hands-on in designing, training, and fine-tuning models across traditional ML, deep learning, and preferably GenAI (LLMs, diffusion models, etc.)Collaborate with data scientists to transform exploratory notebooks into scalable, maintainable, and monitored deployments</li>
</ul>

<ul>
<li>Implement CI/CD pipelines, version control, and experiment tracking using tools like MLflow, DVC, or similar</li>
</ul>

<ul>
<li>Do shadow deployment and A/B testing of production models</li>
</ul>

<ul>
<li>Partner with data engineers to build data pipelines that support real-time or batch model inference</li>
</ul>

<ul>
<li>Ensure high availability, performance, and observability of deployed ML solutions using MLOps best practices</li>
</ul>

<ul>
<li>Conduct code reviews, performance tuning, and contribute to ML infrastructure improvements</li>
</ul>

<ul>
<li>Support the end-to-end lifecycle of ML products</li>
</ul>

<ul>
<li>Oversee and mentor large team of associate and junior-level data scientists, de-bottlenecking issues related to project execution</li>
</ul>

<ul>
<li>Contribute to knowledge sharing, reusable component development, and internal upskilling initiatives</li>
</ul>

Required-

<ul>
<li>Bachelor's in Computer Science, Data Science, Statistics, Mathematics, or a related field.</li>
</ul>

<ul>
<li>Master's degree preferred</li>
</ul>

<ul>
<li>Proven experience of 3-6 years as a Data Scientist or in a similar role, with a strong track record of delivering successful data science projects</li>
</ul>

<ul>
<li>Sound theoretical and practical knowledge of working in statistical analysis, machine learning techniques, and deep learning frameworks with solid of understanding of techniques related to regression, classification, NLP, Computer Vision, Generative AI</li>
</ul>

<ul>
<li>Strong programming skills in Python; familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorchHands-on experience with tools like MLflow, Docker, Kubernetes, FastAPI/Flask, Airflow, Git, and cloud platforms (Azure/AWS)</li>
</ul>

<ul>
<li>Proficiency in Python is a must.</li>
</ul>

<ul>
<li>Proficiency in SQL/ spark for data manipulation is a plus</li>
</ul>

<ul>
<li>Worked in developing analytics solutions in 3-4 domains</li>
</ul>

<ul>
<li>Excellent communication skills to effectively manage a team and collaborate with stakeholders in cross-functional teams</li>
</ul>

<ul>
<li>Experience in implementing and productionizing Generative AI applications using LLMs is a plus(e.g., OpenAI, HuggingFace, LangChain, RAG architectures)</li>
</ul>

Data Scientist

India

Roles- Build and deploy production-grade ML pipelines for varied use cases across operations, manufacturing, supply chain, and more Manage analytics strategy across multiple use cases Work hands-on in designing, training, and fine-tuning models across traditional ML, deep learning, and preferably GenAI (LLMs, diffusion models, etc.)Collaborate with data scientists to transform exploratory notebooks into scalable, maintainable, and monitored deployments Implement CI/CD pipelines, version control, and experiment tracking using tools like MLflow, DVC, or similar Do shadow deployment and A/B testing of production models Partner with data engineers to build data pipelines that support real-time or batch model inference Ensure high availability, performance, and observability of deployed ML solutions using MLOps best practices Conduct code reviews, performance tuning, and contribute to ML infrastructure improvements Support the end-to-end lifecycle of ML products Oversee and mentor large team of associate and junior-level data scientists, de-bottlenecking issues related to project execution Contribute to knowledge sharing, reusable component development, and internal upskilling initiatives Required- Bachelor's in Computer Science, Data Science, Statistics, Mathematics, or a related field. Master's degree preferred Proven experience of 3-6 years as a Data Scientist or in a similar role, with a strong track record of delivering successful data science projects Sound theoretical and practical knowledge of working in statistical analysis, machine learning techniques, and deep learning frameworks with solid of understanding of techniques related to regression, classification, NLP, Computer Vision, Generative AI Strong programming skills in Python; familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorchHands-on experience with tools like MLflow, Docker, Kubernetes, FastAPI/Flask, Airflow, Git, and cloud platforms (Azure/AWS) Proficiency in Python is a must. Proficiency in SQL/ spark for data manipulation is a plus Worked in developing analytics solutions in 3-4 domains Excellent communication skills to effectively manage a team and collaborate with stakeholders in cross-functional teams Experience in implementing and productionizing Generative AI applications using LLMs is a plus(e.g., OpenAI, HuggingFace, LangChain, RAG architectures)

Data Scientist · New Delhi

Job highlights

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Job Description

Job Description for Data Scientist

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