Senior Data Scientist - Generative AI

TechRBM is a fast-growing digital transformation partner to global enterprises, delivering solutions across AI, Cloud, Data Engineering, and Automation. We're scaling from 120+ to 300-500 professionals and are building a high-impact Data Science team to ship measurable business outcomes for clients in BFSI, Retail, Healthcare, Manufacturing, and High-Tech. As a Senior Data Scientist at TechRBM, you will be responsible for end-to-end problem-solving, from business discovery and hypothesis design to model deployment and post-production monitoring. Your role will involve partnering with product, engineering, and client stakeholders to build production-grade ML/AI and GenAI solutions on platforms like AWS, Azure, and GCP. Additionally, you will mentor a small pod of data scientists/ML engineers (2-5 members). Key Responsibilities: - Engage with client stakeholders to translate objectives into measurable DS/ML use cases, define success metrics (ROI, adoption, accuracy, latency), and create experiment plans. - Own data acquisition, quality checks, EDA, and feature pipelines across SQL/Spark/Databricks; collaborate with Data Engineering for robust ingestion and transformation. - Build, tune, and compare models for supervised/unsupervised learning, time-series forecasting, NLP/CV, and GenAI using Python, PyTorch/TensorFlow, and other relevant tools. - Productionize models via MLflow/DVC, model registry, CI/CD, containers, and cloud ML platforms. Implement monitoring for drift, data quality, and model performance. - Design and analyze A/B tests, apply causal inference techniques to measure true impact. - Apply model cards, SHAP/LIME, bias checks, PII handling, and ensure compliance with data privacy regulations. - Build insights dashboards and communicate recommendations to senior business and technical stakeholders. - Mentor juniors, conduct code and research reviews, contribute to standards, and support solutioning during pre-sales/POCs. Required Skills & Experience: - 7-10 years overall experience, with 5+ years in applied ML/Data Science for enterprise clients. - Expertise in Python, advanced SQL, Spark/Databricks, and strong software practices. - Familiarity with ML/AI tools like scikit-learn, XGBoost/LightGBM, PyTorch or TensorFlow, and NLP frameworks. - Experience with cloud deployments on AWS/Azure/GCP, MLOps tools, and CI/CD practices. - Proficiency in experimentation, analytics, visualization, and communication. - Exposure to domains like BFSI, retail, healthcare, or manufacturing is a plus. - Knowledge in recommenders, time-series analysis, graph ML, optimization, and geospatial analytics is a bonus. Education & Certifications: - Bachelor's/Master's in Computer Science, Data Science, Statistics, Applied Math, or related field. - Preferred certifications in AWS/Azure/GCP ML, Databricks, TensorFlow, or PyTorch.,