Job Title

Interested candidates, kindly mail to enpcareers.hr@Summary of Role:- Define and develop new data science use cases to support business users by executing strategies that improve business performance through informed decision-making. - Proactively collaborate with operations, technology, and business teams to develop advanced analytics and data models. - Support the development and utilization of data science capabilities (AI/ML models) and coordinate cross-functional analytics initiatives.Job Accountabilities:- Work hands-on with the data science team on innovative business use cases and define how these initiatives will create additional value through the effective utilization of data assets and analytics. - Consistently identify and monitor key business risks and determine the data requirements needed to address them. - Identify and evaluate AI/ML models used by the developer community for integration into business use cases. - Drive awareness, education, and adoption of data science across the organization by communicating the vision and use cases of advanced analytics. - Manage external data and analytics partners and play a key role in the development and design of the department's vision, capabilities, infrastructure, and quarterly/annual roadmap for launching data science capabilities. - Support scope definition, design, and implementation of machine learning models to enable various initiatives and programs aligned with overall objectives and targets. - Formulate and optimize algorithms fundamental to the business's products and services, identifying solutions that enhance stakeholder experience. - Collaborate with business teams, digital teams, and partners to provide reliable, secure, and cost-effective infrastructure and operational services. - Draft and maintain scope definition documents, concept notes, and other requisite documentation.Skills Required:- Strong proficiency in AI/ML models and concepts, with an understanding of technical architecture. - Solid understanding of machine learning, experimental design, optimization, statistical methods, and modeling algorithms, with hands-on experience in the following:a. Supervised ML Models: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosting (XGBoost / LightGBM / CatBoost)b. Ensemble & Calibration: Bagging, Stacking, Model Ensembling, Calibration (Platt Scaling, Isotonic Regression).c. Time-Series & Forecasting: ARIMA/SARIMA, Exponential Smoothing (ETS), Prophet, Seasonal Decomposition, LSTM/GRU networks, Transformer-based time-series models.d. Deep Learning (Vision/Sequence): CNNs, U-Net/Segmentation networks, Sequence-to-Sequence models, Transformers, BERT/RoBERTa for NLP.e. Unsupervised & Representation Learning: K-Means, Hierarchical Clustering, DBSCAN, PCA, Autoencoders, t-SNE/UMAP.f. Probabilistic & State-Space Models: Gaussian Processes, Hidden Markov Models (HMM), Kalman Filters.3.Excellent documentation and presentation skills.Experience Required:- Minimum of 10+ years of experience in Data Science. - Degree from a reputed institute in Computer Science, Data Science, Statistics, or Mathematics is preferred.Interested candidates, kindly mail to enpcareers.hr@