Sr. Data Scientist

What is the opportunity?

The Alternative Data & AI team works with clients and leverages alternative data (structured and unstructured non-financial data) datasets and applying advanced AI techniques to develop financially relevant factors, actionable insights, and differentiated content for Capital Markets clients.

The Sr. Data Scientist on this team plays a key role in delivering AI and data-driven solutions to our Institutional Research stakeholders and clients, driving innovation at the intersection of alternative data and cutting-edge machine learning.

• Lead the design and implementation of statistical, machine learning, and mathematical methodologies to solve complex research problems and perform advanced data analysis leveraging alternative datasets.
• Identify and evaluate novel data sources, to develop unique and proprietary insights for institutional research teams and clients — including web scraping, geolocation data, satellite imagery, NLP on unstructured data sources (such as news), and other non-traditional signals.
• Collaborate closely with equity and macro research teams, technology teams, and cross-functional stakeholders on strategic initiatives, providing expertise in advanced analytics, data modelling, data cleansing, and data optimization.
• Build, maintain, and enhance data pipelines and infrastructure using Databricks, Snowflake, PySpark, and SQL to ensure scalable, reliable, and efficient data processing across large alternative datasets.
• Champion emerging technology trends and tools that can be leveraged to further the Alternative Data & AI platform, staying current with developments in generative AI, large language models, and alternative data sourcing.
• Coordinate, generate, and maintain alternative data products, presentations, models, and databases of unique, alternative, and proprietary insights that support client-facing research.
• Drive the development of big data and alternative data capabilities, leading coordination of cross-functional engineering and research initiatives within the Alternative Data & AI team.
• Design and develop proprietary indices and factor models, applying rigorous quantitative methodologies to construct, backtest, and maintain financially relevant indices derived from alternative data signals.
• Proactively identify new opportunities for engaging Research teams with novel data products and AI-driven analytical frameworks.
• Mentor and develop junior data scientists, providing technical guidance during project execution and fostering a culture of continuous learning within the team.
• Provide senior-level research support to stakeholders as required, acting as a subject matter expert on alternative data methodologies, index construction, and AI-driven analytics.

• Proactively identify operational risks and control deficiencies in the business.
• Review and comply with Firm Policies applicable to your business activities.
• Escalate operational risk loss events, control deficiencies, and risks to your line manager and the relevant risk and control functions on a timely basis.

• Master's or PhD in Mathematics, Statistics, Computer Science, or another quantitative field.
• 3+ years of experience in Data Science, Machine Learning, Natural Language Processing, or Statistics — ideally in a capital markets or financial research context.
• Strong quantitative modelling skills, including statistical modelling, machine learning, and optimization techniques applied to financial or alternative datasets.
• Demonstrated ability to perform complex data analysis on large volumes of structured and unstructured data, and to present findings clearly to non-technical stakeholders.
• Hands‑on experience with Databricks for large‑scale data processing and ML workflows, and Snowflake for cloud data warehousing and analytics.
• Strong proficiency in PySpark for distributed data processing and SQL for data querying, transformation, and pipeline development across large datasets.
• Experience in index construction and factor model development, including the design, backtesting, and ongoing maintenance of quantitative indices derived from alternative…