Data Scientist

Role Description

The Data Scientist Senior Analyst plays a key role in embedding advanced analytics and AI-enabled capabilities into day-to-day investment and operational workflows. The role combines business-facing enablement with hands-on solution development—working across teams to improve how data is used, decisions are made, and processes are executed.

The position begins with a strong focus on understanding the firm’s data ecosystem and internal workflows and evolves into designing and building scalable solutions—from workflow automation to more advanced, model-driven applications that support the firm’s broader digital transformation.

Responsibilities

1. Enablement & Use-Case Development

• Partner with teams across front, middle, and back office to identify where automation and AI can improve real workflows.
• Guide business teams in designing and adopting their own enhanced workflows, providing hands-on support, frameworks, and review.
• Structure business problems into clearly defined use cases, including requirements, prioritization, and expected impact.
• Maintain and track a centralized pipeline of initiatives, including progress, adoption, and outcomes (e.g., efficiency gains, quality improvements).

2. Solution Development & Automation

• Design and build practical solutions that enhance workflows, including automation, data-driven tools, and intelligent assistants.
• Develop and deploy AI-supported applications (e.g., agents, document/query solutions) with appropriate controls and reliability considerations.
• Support implementation of retrieval and knowledge-access solutions that make internal data and content more usable.
• Integrate solutions with internal systems and support end-to-end automation of recurring processes.

3. Data Landscape & Foundations

• Build a deep understanding of the firm’s data architecture, including internal systems, vendor platforms, and document repositories.
• Map key data sources and flows to ensure solutions are grounded in what the data can support.
• Identify and help address gaps in data accessibility, quality, and structure that impact analytics and automation use cases.

4. Stakeholder & Delivery Management

• Act as a bridge between business stakeholders and technical or external partners.
• Support delivery and implementation efforts through hands-on involvement, review, and coordination.
• Contribute to evaluation and onboarding of new tools and platforms, including initial assessment of data handling considerations.

5. Continuous Development & Innovation

• Stay up to date with developments in investment management, data, and applied AI.
• Contribute to evolving the firm’s capabilities by progressively taking on more advanced technical and solution-building responsibilities.

Skills

• Investment Management
• Business & Use-Case Structuring
• Data Analysis & Automation
• Workflow Optimization
• Stakeholder Management
• Communication
• Applied AI / Emerging Technologies

Requirements

• Bachelor’s or master’s degree in finance, Economics, Business, Computer Science, Management Information System or a related field.
• 4–7 years of experience combining investment domain knowledge with hands-on analytics, automation, or AI-related work.
• Proven ability to deliver practical solutions (e.g., automation, reporting tools, intelligent workflows) that are adopted by end users.
• Strong ability to translate between business needs and technical requirements.
• Familiarity with tools such as SQL, Python, or similar; experience working with data-driven workflows is preferred.
• Strong communication skills and experience working across cross-functional teams.
• High ownership mindset, with comfort operating in evolving and ambiguous environments.