Data Science & AI/ML Jobs

Join Clarion Partners' Research & Strategy team to build, test, and maintain statistical and machine-learning models that inform commercial real estate investment decisions. You'll analyze structured and semi-structured datasets, maintain forecasting and ranking models in production, and contribute to experiments and feature development. The role involves collaborating with global teams, documenting methods clearly, and maintaining shared codebases and data pipelines.

Senior Data Scientist to lead technical research and analytics supporting global real estate investment decisions. You will manage and mentor a growing analytics team in Hyderabad, design and productionize statistical, machine learning, and AI models, and build forecasting and ranking systems. The role requires translating model outputs into risk and portfolio frameworks, driving MLOps and data pipeline improvements, and communicating quantitative insights to global stakeholders.

Join the Data Science team to develop predictive models and machine learning solutions that support portfolio optimization, scenario analysis, and risk forecasting. Work with large-scale financial datasets, implement time-series and portfolio optimization algorithms, and apply NLP and generative AI for research automation. Build ML pipelines, dashboards, and visualization tools while collaborating closely with portfolio managers, research analysts, and technology teams to deliver actionable investment insights.

Morgan Stanley's Firm Risk Management is hiring a Vice President to develop and deploy Python-based AI/ML applications for risk analytics, including NLP pipelines and LLM tools. The role involves managing a small development team, applying software engineering best practices, and delivering production-grade solutions integrated with Risk Management workflows. The candidate will collaborate with stakeholders across Risk Analytics, Technology, and Strats and contribute to model and system design decisions.

The Portfolio and Quantitative Analytics Analyst will support Lazard Wealth's investment teams by delivering portfolio analytics, performance attribution, risk reporting and quantitative modelling. The role involves data analysis, preparing client reporting, building tools and models, and collaborating closely with portfolio managers and IT. Strong quantitative skills, attention to detail and proficiency with Excel and programming (e.g. Python/R/SQL) are expected. This is an early-career role based within the Lazard Wealth team with opportunities to develop technical and investment expertise.

Senior role leading portfolio and quantitative analytics for Lazard Wealth. Responsible for developing portfolio construction and risk models, performing quantitative research and analysis, and translating results for investment teams and client-facing stakeholders. Collaborates across investment, technology and advisory teams to implement analytics solutions and support wealth management strategies. Requires strong quantitative, programming and communication skills to drive data-driven investment decisions.

Join the Treasury Analytics team to lead deposit insights and liquidity analytics for a $1+ trillion retail deposit portfolio. You will collaborate across Treasury, Liquidity Risk, Data & Analytics and Finance to develop customer segmentation, stress methodologies, and repeatable intelligence processes. The role requires presenting high-impact analysis to senior leaders, influencing strategy, and mentoring junior talent. Strong data tooling skills and a consultative mindset are key to driving liquidity initiatives and improving analytical frameworks.

Join JPMorgan Chase's Consumer & Community Banking Machine Learning team as an Applied AI Engineer-Associate to build and scale production-grade machine learning platforms and solutions. You will develop secure, high-quality production code, architect next-generation ML models and systems, and drive ML Ops and cloud-native architectures. The role requires hands-on experience with Python/Java, cloud platforms (AWS/GCP/Azure), ML frameworks, AI agents/RAG solutions, and strong communication to influence technical and business stakeholders.

Join the Wholesale Credit team to design, analyze, and deliver quantitative models supporting wholesale credit stress testing (CCAR, ICAAP), loan loss reserves, and PPNR forecasting. You will apply statistical and time-series techniques to large panel datasets, build forecasting models, and collaborate with business partners and senior quantitative researchers. The role emphasizes practical knowledge of generalized linear models, clustering, decision trees, logistic regression, and proficiency in Python or R. This position offers exposure to regulatory modeling and credit risk concepts within a large banking environment.

Join the Payments Digital & Design team to build analytics solutions that drive business impact across payments and digital products. You will analyze large datasets, prototype ML models, and develop automated dashboards and analytics products to inform strategy and senior management reporting. The role combines data science, product management, and consulting skills, and requires strong communication to present insights to stakeholders.