Senior Data Scientist

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Summary of Role:

1. Define and develop new data science use cases to support business users by executing strategies that improve business performance through informed decision-making.
2. Proactively collaborate with operations, technology, and business teams to develop advanced analytics and data models.
3. Support the development and utilization of data science capabilities (AI/ML models) and coordinate cross-functional analytics initiatives.

Job Accountabilities:

1. 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.
2. Consistently identify and monitor key business risks and determine the data requirements needed to address them.
3. Identify and evaluate AI/ML models used by the developer community for integration into business use cases.
4. Drive awareness, education, and adoption of data science across the organization by communicating the vision and use cases of advanced analytics.
5. Manage external data and analytics partners and play a key role in the development and design of the departments vision, capabilities, infrastructure, and quarterly/annual roadmap for launching data science capabilities.
6. Support scope definition, design, and implementation of machine learning models to enable various initiatives and programs aligned with overall objectives and targets.
7. Formulate and optimize algorithms fundamental to the businesss products and services, identifying solutions that enhance stakeholder experience.
8. Collaborate with business teams, digital teams, and partners to provide reliable, secure, and cost-effective infrastructure and operational services.
9. Draft and maintain scope definition documents, concept notes, and other requisite documentation.

Skills Required:

1. Strong proficiency in AI/ML models and concepts, with an understanding of technical architecture.
2. 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:

1. Minimum of 10+ years of experience in Data Science.
2. Degree from a reputed institute in Computer Science, Data Science, Statistics, or Mathematics is preferred.

Interested candidates, kindly mail to