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Tier-1 brand plus senior mid-level role with niche ML/LLM focus yields moderate applicant competition.
High because role demands specialized ML/NLP/LLM expertise and financial data domain experience.
Explicit 8–12 years, leadership, production ML, NLP/LLM, cloud and MLOps requirements increase filtering strictness.
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Lead and mentor a team of senior data scientists, driving end-to-end delivery of AI/ML projects including model development, deployment, and continuous optimization.
Own and refine an advanced data management and analytics platform focused on financial analytics, integrating data acquisition, transformation, quality control, and workflow automation.
Partner with senior business stakeholders and cross-functional teams to translate business needs into scalable AI/NLP/LLM solutions with clear success metrics and alignment across functions.
8-12 years of experience in data science or related analytics and statistical modeling roles.
Master’s degree in Statistics, Mathematics, Computer Science with Data Science certification, or Engineering degree specializing in Data Science/AI.
Strong expertise in AI/ML techniques including deep learning, NLP, LLMs, RAG, and data engineering with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Experience with cloud platforms (AWS, Azure), MLOps, CI/CD pipelines, and production deployment of AI/ML models.
Experienced in financial services or investment banking environments with strong understanding of relevant domain content and business processes.
Proven track record of strategic technical leadership including defining AI governance, ethics, risk frameworks, and leading multi-team or matrixed organizations.
Demonstrated ability to drive high-impact, scalable AI/ML solutions by bridging technical expertise with business strategy and cross-functional stakeholder management.