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.