Alpha Data Services – Senior Data Analyst

Alpha Data Services – Senior Data Analyst – AVP

Alpha Data Services seeks a team‑oriented Senior Data Analyst with strong experience and a passion for building Data Insight and Analytics capabilities. This role supports the growing demand within Alpha Data Services and across our client base. State Street is making a multi‑year strategic investment in Alpha Data Services. We require a strong data science and analytics practitioner to work internally and with clients and prospects to design, build, and scale new Data Insight and Analytics capabilities. This role is critical to enabling evidence‑based decision‑making, accelerating product development, and supporting the refinement of our multi‑year Alpha strategy. The Senior Data Analyst will be responsible for collecting, analysing, and interpreting large and complex datasets to provide actionable insights. This role requires deep analytical expertise, exceptional attention to detail, and the ability to clearly communicate findings to senior stakeholders. This role is central to improving the integrity, velocity, and quality of data used across Alpha’s implementation, product, and client delivery functions. A strong understanding of financial data structures—particularly account reference data classifications not currently well-supported through RDP or ACM—and hands‑on analytics development experience is essential. Responsibilities

• Data Quality & Governance:
• Lead the design and execution of data insight and analytics capabilities across Alpha client datasets to support testing efficiency, accelerate insights, and enhance data driven decision making.
• Perform advanced analytics and modelling to address emerging and current business needs across multiple product and functional areas.
• Define data requirements and lead data collection, processing, cleaning, analysis, modelling, and visualisation activities across structured and unstructured datasets.
• Develop analytical toolkits, reusable components, and research techniques to support ongoing service delivery and product innovation.
• Data Quality, Reference Data & Operational Insight
• Analyze client and internal datasets to identify trends, patterns, and anomalies, providing clear recommendations to improve decision‑making.
• Support classification‑based account reference data needs that require enhanced modelling and handling beyond the current capabilities of RDP and ACM.
• Identify opportunities to improve operational efficiency, including the measurement of data quality uplift, issue frequency, and impact.
• Provide implementation teams with holistic data insights to accelerate onboarding timelines and improve end‑to‑end data understanding within client environments.
• Reporting, Visualisation & Tooling
• Design, develop, and maintain complex, scalable visualisation solutions (e.g., dashboards, analytics models, reporting suites).
• Work collaboratively with cross‑functional teams to define meaningful dashboards and reporting that adds measurable value.
• Stakeholder Engagement
• Present insights clearly to senior leadership, clients, and prospects across a range of technical and non technical audiences.
• Act as a strategic partner to domain leads, contributing analytics expertise to product development, service evolution, and client engagements.
• Provide context and analytics around issue severity, volume, and prioritisation to guide team focus and track improvement over time. •

Skills & Attributes Strong analytical mindset with the ability to break down complex problems.

• Strong analytical mindset with the ability to break down complex problems.
• Advanced quantitative skills, including strong mathematics and statistics.
• Demonstrated expertise in identifying trends and patterns within large datasets.
• Strong proficiency in Python, R, and SQL with the ability to build robust analytical solutions.
• Proven experience across the full data science lifecycle:
• Stakeholder engagement
• Data wrangling
• Modelling
• Delivering insights and visualisations
• Confident ability to tell compelling stories with data, tailoring messages to senior leaders and client stakeholders.
• Excellent influencing, communication, and collaboration skills.
• Creative problem solver with a practical and solution-oriented mindset.
• Ability to create clear, intuitive visual displays of data.
• Leadership capabilities, including coaching or mentoring team members.

Education & Preferred Qualifications

• Minimum of 10 years’ data science or analytics experience within an Asset Manager or financial services environment.
• Degree in Computer Science, Statistics, Operational Research, or a related field, with