Data Scientist

Job Description: Data Scientist (MLOps, CI/CD, Generative AI) 
Experience : 4 to 6 Years
Location: Isb / Hybrid

About the Role 

We are seeking a Full Stack Data Scientist with strong expertise in MLOps, CI/CD, and Generative AI to join our growing AI/ML team. This role is highly dynamic and requires a balance of technical excellence, customer-facing skills, and business acumen. 

You will be responsible for the end-to-end machine learning lifecycle—from data exploration and model development to deployment and optimization. A key part of the role is engaging with customers, understanding their business challenges, and delivering impactful Proof of Concepts (POCs) that build trust and demonstrate value. 

Candidates with hands-on expertise in statistical models, traditional ML, deep learning architectures, time series forecasting, and financial modeling will be strongly preferred. 

Experience with GPUs, CUDA, and high-performance computing is a plus, given the scale and complexity of deep learning and Generative AI workloads. 

Key Responsibilities 

• Engage directly with customers to understand business problems and translate them into data science solutions. 

• Design and deliver impactful projects that clearly demonstrate value and help win new business opportunities. 

• Build and deploy end-to-end ML/AI solutions across domains such as NLP, Computer Vision, Generative AI, and Forecasting. 

• Develop and optimize MLOps pipelines for model training, deployment, and monitoring with CI/CD best practices. 

• Implement statistical, traditional ML, and deep learning models, ensuring accuracy, scalability, and robustness. 

• Create time series and financial forecasting models for predictive analytics in business and finance use cases. 

• Apply Generative AI methods (LLMs, RAG, LangChain, Hugging Face, Diffusion Models) to enterprise use cases. 

• Optimize training and inference with GPU acceleration and CUDA where applicable. 

• Ensure production-grade deployment with monitoring, drift detection, and retraining strategies. 

• Collaborate with product managers, engineers, and stakeholders to align technical solutions with business outcomes. 

• Stay updated with industry trends and bring innovative AI/ML solutions to customer engagements. 

Required Qualifications 

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field. 

• Experience: 3+ years of professional experience in end-to-end ML/AI solution delivery. 

• Technical Expertise: 

• Statistical models (hypothesis testing, regression, time series analysis). 

• Traditional ML (SVM, decision trees, ensemble methods, clustering, recommendation systems). 

• Deep Learning (CNNs, RNNs, LSTMs/GRUs, Transformers, GANs, Diffusion Models). 

• Time Series & Financial Models (ARIMA, Prophet, advanced LSTM/GRU models, risk prediction). 

• Generative AI (LLMs, RAG, LangChain, Hugging Face Transformers, OpenAI APIs). 

• Proficiency in Python (NumPy, Pandas, Scikit-learn, Statsmodels, TensorFlow, PyTorch). 

• Hands-on experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI). 

• Strong knowledge of CI/CD workflows (GitHub Actions, GitLab CI, Jenkins, Azure DevOps). 

• Experience with cloud platforms (AWS, Azure, GCP) for ML deployment and scaling. 

• Strong understanding of Docker, Kubernetes, and production deployment. 

• Excellent communication and presentation skills to face customers confidently. 

• Proven ability to translate customer requirements into POCs and production solutions.. 

Preferred/Bonus Skills 

• Experience with GPUs, CUDA, and high-performance model training. 

• Familiarity with real-time inference frameworks (TensorRT, Triton, TorchServe, FastAPI). 

• Knowledge of feature stores (Feast, Tecton) and monitoring tools (Evidently, WhyLabs, Prometheus, Grafana). 

• Exposure to financial services, supply chain, or enterprise AI domains. 

• Track record of winning client trust through successful POCs and solution delivery. 

• Contributions to open-source ML/AI projects.