Data Scientist

We are seeking a talented Data Scientist to join our on-site team in Ahmedabad, India. This role is crucial for the end-to-end lifecycle of our machine learning models, from initial development and validation to deployment and ongoing operational monitoring. You will be instrumental in designing and building production-ready ML models, including data ingestion, feature engineering, model training, and deployment. Your responsibilities will involve translating complex business challenges into actionable analytical solutions, selecting appropriate modeling techniques and evaluation metrics, and implementing efficient data pipelines and reproducible experiments using Python and modern data tools. You will collaborate closely with engineers to integrate models into production systems, conduct rigorous model validation, A/B testing, and bias/fairness checks to ensure performance meets stringent latency and accuracy Service Level Agreements (SLAs). Effective communication is key; you will create clear technical documentation, present model insights to stakeholders, and work with product teams to embed machine learning capabilities into our offerings. Continuous monitoring of model performance in production, implementing retraining strategies, and addressing data or concept drift issues are also integral parts of this role. We are looking for individuals proficient in Python, SQL, Pandas, NumPy, scikit-learn, and TensorFlow. Experience with PyTorch, Spark, Docker, MLflow, and AWS is preferred. A proven track record of building and deploying ML models, coupled with 2-6 years of hands-on experience in data science or applied ML roles, a strong statistical foundation, experience with experimental design and model evaluation, and the ability to work collaboratively on-site are essential. This position offers the opportunity to work on high-impact enterprise ML projects with direct business ownership in a learning-oriented environment that includes mentoring, technical workshops, and access to modern tooling, all within a compact, performance-driven analytics team.