Posted Apr 28, 2026
As an AI/ML Solution Lead, your role involves leading end-to-end solutioning for AI/ML projects within Financial Services. You will collaborate with business and product teams to identify impactful use cases, build scalable ML models using Python and frameworks like Scikit-learn and TensorFlow, and deploy solutions on cloud platforms. Your responsibilities include:
Leading AI/ML solutioning from problem framing to deployment, focusing on Financial Services industries. - Building and productionizing scalable ML models and pipelines using Python and ML frameworks. - Driving feature engineering, model evaluation, and performance optimization aligned with business KPIs. - Deploying ML solutions on cloud platforms like AWS, Azure, or GCP using MLOps frameworks and CI/CD best practices. - Translating technical insights into business-friendly narratives for senior stakeholders. - Mentoring and guiding junior data scientists and ML engineers to foster a culture of learning and innovation. - Staying updated on emerging trends in AI to evaluate their applicability to business problems. Qualifications required for this role include:
8-12 years of overall experience with at least 5 years in applied Machine Learning. - Proven track record of delivering AI/ML projects with measurable business outcomes. - Proficiency in Python and key ML libraries (Scikit-learn, TensorFlow, PyTorch). - Hands-on experience deploying models on cloud platforms like AWS, Azure, or GCP. - Familiarity with data pipelines, APIs, and cloud-native architectures. - Exposure to BFSI use cases such as credit risk modeling, fraud detection, churn prediction, customer segmentation, or marketing analytics. - Strong foundation in statistics, probability, and linear algebra. - Excellent communication, presentation, and stakeholder management skills. - Educational background in Engineering, Computer Science, Mathematics, Statistics, or related fields (MBA or Master's in Data Science preferred). - Curiosity about AI innovation, experimentation, and emerging technologies. As an AI/ML Solution Lead, your role involves leading end-to-end solutioning for AI/ML projects within Financial Services. You will collaborate with business and product teams to identify impactful use cases, build scalable ML models using Python and frameworks like Scikit-learn and TensorFlow, and deploy solutions on cloud platforms. Your responsibilities include:
Leading AI/ML solutioning from problem framing to deployment, focusing on Financial Services industries. - Building and productionizing scalable ML models and pipelines using Python and ML frameworks. - Driving feature engineering, model evaluation, and performance optimization aligned with business KPIs. - Deploying ML solutions on cloud platforms like AWS, Azure, or GCP using MLOps frameworks and CI/CD best practices. - Translating technical insights into business-friendly narratives for senior stakeholders. - Mentoring and guiding junior data scientists and ML engineers to foster a culture of learning and innovation. - Staying updated on emerging trends in AI to evaluate their applicability to business problems. Qualifications required for this role include:
8-12 years of overall experience with at least 5 years in applied Machine Learning. - Proven track record of delivering AI/ML projects with measurable business outcomes. - Proficiency in Python and key ML libraries (Scikit-learn, TensorFlow, PyTorch). - Hands-on experience deploying models on cloud platforms like AWS, Azure, or GCP. - Familiarity with data pipelines, APIs, and cloud-native architectures. - Exposure to BFSI use cases such as credit risk modeling, fraud detection, churn prediction, customer segmentation, or marketing analytics. - Strong foundation in statistics, probability, and linear algebra. - Excellent communication, presentation, and stakeholder management skills. - Educational background in Engineering, Computer Science, Mathematics, Statistics, or related fields (MBA or Master's in Data Science preferred). - Curiosity about AI innovation, experimentation, and emerging technologies.
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