Senior Data Scientist - AI/ML

As a Senior Data Scientist, your role will involve solving complex business problems using advanced AI/ML techniques in areas such as credit risk, fraud detection, collections, and customer analytics. You will collaborate closely with business leaders and cross-functional teams to design, build, and deploy machine learning models that drive significant business impact.

Key Responsibilities:

• Develop and deploy machine learning models for various domains including credit risk, fraud detection, customer analytics, and operational optimization.
• Manage the entire machine learning lifecycle from data exploration, feature engineering, model development, validation, deployment, monitoring, to model retraining.
• Create predictive models like risk scorecards, propensity models, recommendation systems, and optimization models.
• Utilize structured and unstructured datasets to derive actionable insights.
• Collaborate with business stakeholders, product teams, and data engineers to transform business challenges into data-driven solutions.
• Monitor model performance to ensure accuracy, scalability, and readiness for production.
• Effectively communicate analytical insights and recommendations to both technical and non-technical stakeholders.

Technical Skills & Requirements:

• 4 - 6 years of experience in Data Science, Machine Learning, or Advanced Analytics.
• Proficiency in Python programming for machine learning and data analysis.
• Strong understanding of SQL for data extraction and manipulation.
• Experience with machine learning frameworks like scikit-learn, TensorFlow, or PyTorch.
• Familiarity with supervised and unsupervised learning techniques.
• Hands-on experience in building models such as risk scorecards, fraud detection models, propensity models, or NLP models.
• Sound knowledge of statistics, predictive modeling, and data analysis techniques.
• Experience working with large structured and unstructured datasets.

Educational Qualifications:

• B. Tech / B.E / BCA / B.Sc / M.Tech / MCA in Computer Science, Mathematics, Statistics, Engineering, or a related field. As a Senior Data Scientist, your role will involve solving complex business problems using advanced AI/ML techniques in areas such as credit risk, fraud detection, collections, and customer analytics. You will collaborate closely with business leaders and cross-functional teams to design, build, and deploy machine learning models that drive significant business impact.

Key Responsibilities:

• Develop and deploy machine learning models for various domains including credit risk, fraud detection, customer analytics, and operational optimization.
• Manage the entire machine learning lifecycle from data exploration, feature engineering, model development, validation, deployment, monitoring, to model retraining.
• Create predictive models like risk scorecards, propensity models, recommendation systems, and optimization models.
• Utilize structured and unstructured datasets to derive actionable insights.
• Collaborate with business stakeholders, product teams, and data engineers to transform business challenges into data-driven solutions.
• Monitor model performance to ensure accuracy, scalability, and readiness for production.
• Effectively communicate analytical insights and recommendations to both technical and non-technical stakeholders.

Technical Skills & Requirements:

• 4 - 6 years of experience in Data Science, Machine Learning, or Advanced Analytics.
• Proficiency in Python programming for machine learning and data analysis.
• Strong understanding of SQL for data extraction and manipulation.
• Experience with machine learning frameworks like scikit-learn, TensorFlow, or PyTorch.
• Familiarity with supervised and unsupervised learning techniques.
• Hands-on experience in building models such as risk scorecards, fraud detection models, propensity models, or NLP models.
• Sound knowledge of statistics, predictive modeling, and data analysis techniques.
• Experience working with large structured and unstructured datasets.

Educational Qualifications:

• B. Tech / B.E / BCA / B.Sc / M.Tech / MCA in Computer Science, Mathematics, Statistics, Engineering, or a related field.