Senior Associate – Data Science

1 week ago

bangalore, India Publicis Sapient Full time

Role: Senior Associate – Data Science & Machine Learning Experience: 5 to 8 Years Work Mode: Hybrid (3 days office per week) Location: Gurugram (GGN)/Bengaluru (BEN) Notice Period: Immediate to 2 weeks ONLY Employment Type: Full-Time About the Role We are seeking an experienced Data Science & Machine Learning Engineer who can design, build, and deploy advanced ML and AI-driven solutions. This role demands deep technical expertise in ML algorithms, deep learning architectures, LLMs, and model operationalization on cloud platforms. Key Responsibilities Build predictive models using classification, regression, clustering, and time-series techniques. Perform feature engineering, algorithm selection, hyperparameter tuning, and model evaluation. Build deep learning models using PyTorch or TensorFlow (CNNs, RNNs, transformers). Develop GenAI applications using embeddings, LLMs, prompt engineering, RAG pipelines, LangChain, LlamaIndex, HuggingFace models. Design and implement end-to-end ML pipelines from ingestion to deployment. Build scalable data pipelines and work with cloud-based ML platforms (AWS/GCP/Azure ML). Deploy, monitor, and maintain ML models using MLOps tools and CI/CD workflows. Work closely with product and engineering teams to integrate ML solutions. Must-Have Skills Strong fundamentals: Statistics, Probability, Linear Algebra, Optimization Machine Learning: Classification, Regression, Clustering Model evaluation (AUC, F1, Recall, ROC curves) Cross-validation, bias-variance trade-off Deep Learning: CNNs, RNNs, Transformers Hands-on PyTorch / TensorFlow GenAI & NLP: LLMs (GPT, LLaMA, Claude, etc.) Embeddings, RAG, vector databases Prompt engineering, model fine-tuning Programming: Python (NumPy, Pandas, Scikit-learn) PyTorch/TensorFlow SQL MLOps: CI/CD Model deployment & monitoring Lifecycle management Version control (Git) and cloud ML platforms (AWS/GCP/Azure) Good to Have Experience with Hugging Face models Knowledge of Docker/Kubernetes Exposure to reinforcement learning Experience with A/B testing or experimentation frameworks Required Candidate Information (For screening – mandatory) Total Experience Relevant DS/ML Experience Current CTC Expected CTC Notice Period (Immediate – 2 weeks only ) Current Location Preferred Location LinkedIn Profile URL How to Apply Send your updated CV to:

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