<ul>
<li>Lead the design and implementation of scalable AI projects. Come up with architecture that support large-scale model deployment, automation of ML workflows, and real-time data processing using cloud-native technologies (AWS, Azure, GCP).</li>
</ul>

<ul>
<li>Spearhead the development and implementation of Generative AI solutions for diverse applications such as text to query, search and summarization, chatbot, autonomous agents</li>
</ul>

<ul>
<li>Serve as a technical advisor to clients, guiding them on best practices in architecture, platform selection, and the end-to-end deployment of ML/AI solutions.</li>
</ul>

<ul>
<li>Oversee the transition of models from proof-of-concept to production environments, ensuring performance, scalability, and maintainability.</li>
</ul>

<ul>
<li>Work closely with product, engineering, and business teams to ensure alignment between data-driven strategies and overall business goals. Collaborate with data engineers and IT teams to ensure robust data pipelines and infrastructure.</li>
</ul>

<ul>
<li>Ensure data governance, privacy, and compliance requirements are adhered to throughout model deployment and operation.</li>
</ul>

<ul>
<li>The person should be driven by a strong desire to continuously learn and to mentor the team, fostering their growth and the growth of Data Science practice.</li>
</ul>

What do we expect

<ul>
<li>15+ years in Data Science, AI, and ML, with a strong focus on production-scale environments and AI/ML platform development with recent experience in Generative AI technologies</li>
</ul>

<ul>
<li>Strong analytical skills with proficiency in the application of statistical analysis and machine learning algorithms like Linear Regression, Logistic Regression, Random Forest, Boosting Trees, SVM, ARIMAX, LSTM, Deep Learning etc.</li>
</ul>

<ul>
<li>Strong experience in AI/ML frameworks (TensorFlow, PyTorch, Keras), MLOps practices, and automation tools for continuous model deployment and monitoring.</li>
</ul>

<ul>
<li>Proficient in big data technologies (Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and modern data architectures (data lakes, data warehouses).</li>
</ul>

<ul>
<li>Programming proficiency in Python, R, and experience with containerization technologies (Docker, Kubernetes).</li>
</ul>

<ul>
<li>Enthuse to collaborate with various stakeholders across the organization and take complete ownership of deliverables.</li>
</ul>

<ul>
<li>Experience solving high business value problems using AI for Retail/CPG/BFSI/Pharma</li>
</ul>

Data Science in Bengaluru (UID-7041)

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Job Description for Data Science

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