Data Scientist (A)

We are seeking an experienced and highly skilled Senior Data Scientist to join our team in Bengaluru. This role focuses on driving innovative, large-scale solutions using cutting-edge Classical Machine Learning, PySpark, Spark SQL, and Generative AI. The ideal candidate will possess a blend of deep technical expertise, strong business acumen, effective communication skills, sense of ownership & be motivated towards establishing quantifiable business impact. We require a proven track record in designing, developing, and real-time deploying scalable ML/DL pipelines and LLM Agents in a fast-paced, collaborative environment. Large-Scale Data Handling, PySpark, & Databricks Deployment efficiently handle and model billions of data points using multi-cluster data processing frameworks (PySpark, Spark SQL). Expertise on Databricks/AWS is a must have: Ability to design, write, scale, and monitor end-to-end ML Pipelines on Databricks/AWS. Proven expertise to run and manage Databricks data pipelines in real time for low-latency decision-making. Develop and implement scalable deployment pipelines using Docker and AWS services (ECR, Lambda, Step Functions). Owning the entire workstreams end to end, from initial designs & POC by building custom machine learning solutions as needed till the business impact calculation of the use-case while ensuring modularity, scalability, and production-ready codebase. Design and implement custom models, loss functions and be able to handle nuanced conversations of trade offs between various modelling choices. Apply specialized modeling for marketing scenarios (Targeting, Budget optimisation, Churn) and data limitations (Sparse/incomplete labels, Single class learning). Practical experience in building LLM-ready Data Management layers for large-scale structured and unstructured data. Apply foundational understanding of LLM Agents and multi-agent systems (e.g., Agent-Critique, ReACT, Agent Collaboration), advanced prompting, LLM evaluation, confidence grading, and Human-in-the-Loop systems. Must Have Technical Skills: Data Pipelines, PySpark & Databricks Proficiency in Python and its data science ecosystem (NumPy, Pandas, Dask, PySpark) for large-scale data processing. Expert, hands-on experience with Databricks for MLOps, pipeline orchestration, and real-time deployment. Ability to perform effective feature engineering by understanding complex business objectives. Core Machine Learning & Deep Learning: In-depth knowledge of Tree Based Models, GLMs', Clustering Models etc. Deep Learning : ANN, 1D/2D/3D Convolutional Neural Networks (ConvNets), LSTMs, Transformer models. Strong proficiency in PU learning, single-class learning, representation learning, alongside traditional ML approaches. Advanced understanding and application of model explainability techniques (e.g., SHAP, LIME). Hands-on experience with ML/DL libraries such as Scikit-learn, TensorFlow/Keras, and PyTorch. Others: Experience utilizing large-scale language models (GPT-4, Mistral, Llama, Claude) through prompt engineering and custom fine tuning. Code Versioning Systems : Github, Git

Having 2 years of experience, all of which relevant into Data Science