Senior Associate – Data Science

2 weeks ago


Tumkūr, 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: 📩 vijay.s@xebia.com



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