Port Enterprise Performance & Risk Implementation Lead

• Experience in buy-side investment management, asset ownership, financial technology, consulting or enterprise software implementation, with direct exposure to portfolio analytics, risk, performance or investment operations.
• Strong understanding of institutional investment workflows, including portfolio management, performance measurement, attribution, risk management and data operations.
• Working knowledge of performance attribution methodologies and ex-ante risk concepts.
• Familiarity with multi-asset portfolios, including fixed income, equities and derivatives.
• Experience leading complex implementations, transformation programmes or strategic client engagements involving multiple stakeholders.
• Ability to analyse discrepancies between expected and observed analytics and explain findings clearly.
• Strong written and verbal communication skills with investment, technical and senior business stakeholders.
• Comfort operating under ambiguity, competing priorities and client pressure.
• Experience working with data feeds, portfolio data structures, analytics outputs and technical integration workflows.
• Exposure to APIs, Python, SQL or other data querying tools.

• Experience with portfolio management, performance attribution, risk analytics or investment management platforms.
• Experience partnering with Product Management and Engineering teams to influence product direction or support enhancements.
• Understanding of modern data architecture, cloud technologies, API ecosystems or data visualisation tools.
• CFA, CAIA or equivalent investment qualification.
• Experience presenting to senior investment, risk or technology stakeholders.
• Knowledge of emerging trends in portfolio analytics, investment operations, data strategy and AI-enabled investment workflows.

Why This Role Matters

PORT sits at the centre of how institutional investors construct portfolios, measure performance, understand risk and make allocation decisions.

Implementation quality directly affects client confidence in analytics used for portfolio construction, capital allocation, risk oversight, performance review and reporting. Strong execution leads to durable adoption and trusted workflows. Weak execution leads to workarounds, misinterpretation and reduced client confidence.

This role owns that outcome.

Investment Analytics Enablement

Internal Influence and Scale

• You invest continuously in deepening your understanding of portfolio analytics, risk models, attribution methodologies, data structures and evolving buy-side practices.

What You'll Need

How Success Is Measured

Depth of understanding and quality of delivery matter more than throughput.

Working at Bloomberg

You will work closely with Product, Engineering, Analytics, Data, Sales and client-facing teams across Bloomberg's buy-side business.

The role rewards intellectual ownership, sound judgement, technical curiosity and the ability to explain complex systems clearly. It offers the opportunity to influence how sophisticated institutional investors use Bloomberg's Performance and Risk capabilities in production, while helping shape the next generation of implementation standards and client workflows.

Apply If

• You want responsibility for how institutional investors use portfolio analytics, performance attribution and risk analytics in practice.
• You are comfortable being accountable for client outcomes, not just project tasks.
• You enjoy combining investment knowledge, technical problem-solving, stakeholder management and delivery execution.
• You want a role where credibility is earned through judgement, clarity, ownership and impact.

You will lead and scale Bloomberg PORT Enterprise implementations for sophisticated buy-side clients across EMEA, with a particular focus on portfolio analytics, performance attribution and ex-ante risk.

This is a senior client-facing implementation role at the intersection of investment workflows, analytics configuration, data integration, programme delivery and adoption. Your work determines whether PORT becomes a trusted production system embedded in live investment decision-making.

You will work directly with portfolio managers, risk teams, performance and attribution specialists, operations, data teams and technology stakeholders to design, configure and deliver solutions that align with each client's investment process and operating model.

This is not a volume implementation role. It requires analytical depth, delivery judgement, technical fluency and the ability to build confidence with senior client stakeholders.

You will not simply configure functionality. You will help clients translate investment requirements, data structures and workflow objectives into a robust operating model supported by Bloomberg's Performance and Risk capabilities.

What You Will Own

• Client Implementations and Delivery
• Lead complex PORT Enterprise and Performance & Risk implementations from discovery through production go-live.
• Define scope, success criteria, delivery milestones and governance with client and internal stakeholders.
• Manage data onboarding, portfolio structures, benchmarks, historical backfills, analytics configuration and validation.
• Make pragmatic implementation decisions when requirements are incomplete, escalating thoughtfully where trade-offs affect delivery, analytics credibility or client outcomes.
• Coordinate across Product, Engineering, Analytics, Data, Sales and other Bloomberg teams to ensure delivery quality and clear ownership.
• Configure portfolio analytics, performance attribution and ex-ante risk workflows to align with client investment processes.
• Translate portfolio construction, factor models, risk assumptions and attribution methodologies into robust system configurations.
• Validate analytics outputs with clients, investigate discrepancies and explain results clearly to both technical and investment audiences.
• Support clients in embedding PORT into daily, monthly, governance and regulatory workflows.

Client Advisory and Adoption

• Act as a trusted counterpart to portfolio managers, risk professionals, performance teams, operations leads and technology stakeholders.
• Facilitate discussions on investment workflows, operating model design and adoption strategy.
• Train users across roles and seniority levels, focusing on practical application rather than feature coverage.
• Drive adoption by helping clients understand how Bloomberg analytics can support better decision-making, oversight and scale.
• Identify recurring client patterns, workflow gaps and edge cases, and translate them into product, process and implementation improvements.
• Partner with Product Management, Engineering and Analytics teams to articulate client needs, validate proposed solutions and support prioritisation where appropriate.
• Contribute to implementation standards, documentation, internal best practice and reusable delivery frameworks.
• Support Sales and Account Management teams with domain credibility during strategic discussions, workshops and proof-of-concepts where relevant.

How You Are Expected to Operate

• This role requires high individual agency, strong analytical judgement and continuous learning.
• You take ownership of open-ended problems and move them forward without waiting for perfect information.
• You make reasoned decisions, test assumptions quickly and adjust based on evidence, client feedback and delivery risk.
• You are comfortable balancing client expectations, commercial context, technical constraints and internal capacity.
• Over time, you are expected to increase your autonomy, influence and impact through reflection, experimentation and learning from both successful and difficult implementations.

Success in this role is measured by:

• Client adoption and sustained usage of PORT analytics
• Accuracy, credibility and explainability of performance and risk outputs
• Quality and timeliness of implementation delivery
• Ability to resolve complex implementation issues efficiently
• Strength of client relationships and stakeholder confidence
• Quality of internal collaboration across Product, Engineering, Analytics, Data and Sales
• Evidence of increasing autonomy, judgement and impact over time
• Contribution to scalable implementation standards and best practice