Data Science Engineer (TCS Walk-in)

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 including Regression, Classification, and Clustering, 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 along with basic understanding of ML model deployment. Strong emphasis is placed on model validation, thorough testing, and proactive issue resolution to ensure reliable, high-quality outputs across the organization.

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 mentoring junior team members and contributing to internal knowledge repositories will also be viewed favorably. Excellent verbal and written communication skills are essential, along with the ability to explain complex technical concepts clearly to both technical and non-technical stakeholders.