Data Science Engineer

The Data Science Engineer will build and deploy end-to-end ML models including training, validation, and deployment. The role involves data preprocessing, feature engineering, data analysis, model evaluation and tuning. The engineer should have expertise in Python with NumPy, Pandas, and Scikit-learn, hands-on experience with ML algorithms, strong knowledge of Statistics and Probability, and proficiency in SQL. Experience in at least one domain such as NLP, Time Series, or Recommendation Systems is required. The role offers the opportunity to work within a collaborative, cross-functional team environment, contributing to end-to-end project delivery and continuous process improvement initiatives. The successful candidate will engage closely with business stakeholders to translate analytical requirements into robust, production-ready data solutions that support long-term organizational growth.

5-10 years of Data Science experience with strong expertise in Python, ML algorithms, Statistics, and SQL. Experience in data preprocessing, feature engineering, model evaluation, and tuning. Exposure to Deep Learning with TensorFlow/PyTorch and cloud platforms. Domain expertise in NLP/Time Series/Recommendation Systems. Any Graduate qualification. Prior experience working in global delivery models, along with exposure to Agile methodologies, will be considered an added advantage. The ideal candidate will bring a proactive, solutions-oriented approach, strong organizational skills, and a commitment to delivering high-quality outcomes within agreed timelines.