Senior Data Scientist

Description :
About The Opportunity : - 5+ Advanced knowledge of Python, SQL and Excel. - R and JavaScript knowledge is nice to have, Experience with typical data science packages : numpy, pandas, matplotlib/seaborn, scikit-learn, scipy, statsmodels, and TensorFlow/Pytorch. - Proven experience handling end-to-end data science projects starting from problem understanding, data cleaning and analysis, modelling, testing and (ideally) deployment. - Knowledge of MLOps principles and tools : cloud technologies, version control, and microservices. - Role : Senior Data Scientist (On-site, India). Role & Responsibilities :
- Lead end-to-end ML projects : translate business problems into technical solutions, design experiments, and deliver production-ready models. - Develop, validate, and optimize supervised and unsupervised models using Python, PySpark, and modern ML frameworks for tabular, time-series, and NLP tasks. - Productionize models : implement deployment pipelines, CI/CD best practices, and ensure model monitoring, retraining, and observability in live environments. - Partner with engineers and product owners to integrate ML services into scalable APIs and data platforms; define SLAs and performance targets. - Drive model governance : implement robust evaluation, bias checks, and documentation for reproducibility and auditability. - Mentor junior data scientists, perform code reviews, and establish engineering standards for reproducible data science workflows. Skills & Qualifications :
Must-Have :
- 5+ Advanced knowledge of Python, SQL and Excel. - R and JavaScript knowledge is nice to have, Experience with typical data science packages : numpy, pandas, matplotlib/seaborn, scikit-learn, scipy, statsmodels, and TensorFlow/Pytorch Proven experience handling end-to-end data science projects starting from problem understanding, data cleaning and analysis, modelling, testing and (ideally) deployment Knowledge of MLOps principles and tools : cloud technologies, version control, and microservices. - Strong proficiency in Python for data science workflows. - Advanced SQL skills for data extraction, validation, and performance tuning. - Experience with PySpark or distributed data processing frameworks. - Practical experience with Scikit-learn and TensorFlow (or equivalent deep-learning frameworks). - Track record of model deployment and productionization, including monitoring and lifecycle management. Preferred :
- Experience with Docker and Kubernetes for containerized deployments. - Familiarity with MLflow or similar model registry and MLOps tooling. - Prior experience in a consulting or client-facing delivery role working with enterprise stakeholders. - Location : India (On-siteAny tier-1 City) If you are a senior-level data scientist who thrives on ownership, productionizing ML, and working closely with clients to solve complex problems, we encourage you to apply.