United Kingdom · Finance · Lead (8-12 years)

Lead Performance Analyst

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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Experience bandLead (8-12 years)
Direct reports3-8 reports
Reports toPerformance Measurement Manager
UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Performance Specialist · Investment Performance Lead · Senior Performance Measurement Analyst

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 1 of 6 standards

Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 1 of 6 standards

iCQ Level 3 Certificate in Providing Financial Services iCan Qualifications Limited · Level 3 · covers 4 of 6 standards

City & Guilds Level 3 Award in Providing Financial Services City & Guilds Limited · Level 3 · covers 3 of 6 standards

NOCN Level 4 Diploma in The Management of Productivity NOCN · Level 4 · covers 1 of 6 standards

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 1 of 6 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England

Measuring the performance of investments iCQ Level 3 Certificate in Providing Financial Services

Performance Measurement & Management NOCN Level 4 Diploma in The Management of Productivity

Data Analysis and Visualisation OTHM Level 7 Diploma in Data Science

The future skills this job leans on

AI Fluency working with AI as a thinking partner

Data Fluency turning numbers into a decision

AI Governance Fluency using AI responsibly

Automation Fluency building AI into how work runs

Systems Fluency seeing the whole picture

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Your Plan Illustration

Built for Lead Performance Analyst

4 units that map to this job, from the qualifications that cover it.

Data Analytics Pearson Education Ltd · covers 1 of 6 standards Level 5
Measuring the performance of investments iCan Qualifications Limited · covers 4 of 6 standards Level 3
Performance Measurement & Management NOCN · covers 1 of 6 standards Level 4
Data Analysis and Visualisation OTHM Qualifications · covers 1 of 6 standards Level 7

These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Lead Performance Analyst?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

Prompt Engineering & LLM Integration
Cloud-Native Data Platforms (e.g., Snowflake, Databricks)

Why each one is rising

The future skills this job leans on

AI Fluencyworking with AI as a thinking partner
Data Fluencyturning numbers into a decision
AI Governance Fluencyusing AI responsibly
Automation Fluencybuilding AI into how work runs
Systems Fluencyseeing the whole picture

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Lead Performance Analyst plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

A Lead Performance Analyst designs and builds reporting systems that measure investment performance. The role involves leading projects, guiding junior analysts, and acting as the go-to expert for complex asset classes or system functionality. It means keeping performance data accurate, useful, and in line with standards such as GIPS.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Excel (VBA, Power Query) Expert

Designing and building complex financial models from scratch for bespoke analysis; writing and debugging advanced VBA macros for automation; mastering Power Query for intricate data transformation and cleaning before it hits our main systems. You're the one setting the standards for how Excel is used.

SQL Advanced

Writing complex multi-join queries, subqueries, and CTEs to extract, transform, and validate data from various data marts; using window functions for advanced calculations; profiling and optimising query performance for critical reports. You'll also be involved in designing database schemas for performance reporting.

Performance Systems (e.g., Eagle PACE, Confluence StatPro, BlackRock Aladdin) Administrator/Strategist

Leading the configuration of new portfolios and composites; designing custom reports and dashboards; troubleshooting complex calculation engine discrepancies; leading vendor selection (RFPs) and managing system implementation/upgrades. You're the primary liaison with the vendor and the internal architect.

Market Data Terminals (e.g., Bloomberg Terminal, FactSet, Refinitiv Eikon) Advanced

Using API tools (e.g., BQL, FactSet's FQL) to pull bulk data into Excel or Python for custom analysis and model inputs; building custom screens and monitors for data validation; understanding the nuances of different data fields and their impact on performance calculations.

BI & Visualization (e.g., Tableau, Power BI) Developer/Architect

Connecting to various data sources (SQL, Python, Excel) and building interactive dashboards from scratch to visualise attribution, risk metrics, and GIPS-related data; governing the firm's BI strategy for performance analytics, including managing server workspaces and data access policies.

Python (with pandas, NumPy, Matplotlib) Leader

Using pandas for advanced data manipulation, cleaning, and analysis that is too complex or repetitive for Excel; automating repetitive reporting tasks and data validation routines; championing the use of Python for advanced analytics (e.g., factor analysis, risk modeling) and setting coding standards for the team.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choice	Coming in	Where you are now	The step above
New Performance Model Design (e.g., for a new asset class)	Assists with data gathering and initial calculations, following a template. No design input.	Proposes minor adjustments to existing models or builds components under guidance. Escalates design choices.	Designs and implements new models independently, seeking feedback on complex elements. Makes technical choices.
GIPS Compliance Interpretation	Applies established GIPS rules to routine reporting tasks. Escalates any ambiguities.	Interprets GIPS guidance for specific, non-routine scenarios. Proposes compliance solutions for review.	Provides definitive interpretations for complex GIPS questions. Recommends policy changes to ensure compliance.
Team Hiring & Onboarding	No involvement beyond perhaps shadowing interviews.	May participate in initial screening or provide feedback on junior candidates.	Conducts technical interviews for junior roles. Provides input on candidate fit and skill gaps.
Budget Allocation for Team Tools/Software	No budget authority. Uses tools provided.	May suggest tools but has no budget authority.	Recommends specific tools or software for project work, with cost estimates, for manager approval.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Project Delivery Rate

Percentage of assigned projects (e.g., new composite builds, system enhancements, GIPS verification prep) completed on time and within scope.

Target · 95% of projects delivered on schedule

Leading the implementation of a new fixed income attribution model, you'd ensure it's live and validated by the agreed-upon Q2 deadline, allowing PMs to use it for their mid-year reviews.

Data Quality Improvement

Reduction in identified data errors or reconciliation breaks originating from performance systems or processes you've designed or overseen.

Target · 15% reduction in critical data errors year-on-year

By designing a more robust data validation script for daily pricing feeds, you've reduced the number of 'stale price' alerts by 20% compared to the previous quarter.

Process Efficiency Gains

Quantifiable reduction in manual effort or processing time for key reporting cycles (e.g., month-end close, quarterly client reporting) through automation or process re-engineering you've led.

Target · 10% reduction in average month-end close time

You implement a Python script that automates a daily data clean-up task, saving the team approximately 2 hours per day, which frees them up for more complex analysis.

GIPS Compliance & Audit Findings

Number of material findings or observations during annual GIPS verification or internal audits related to performance calculation and presentation.

Target · Zero material findings annually

Successfully leading the GIPS verification process for the past year, resulting in a clean report with no material findings, directly protecting the firm's reputation and client trust.

Solution Design Quality

The effectiveness and robustness of new performance reporting solutions, models, or processes you've designed and implemented.

Positive feedback from Portfolio Managers and Risk team on the utility and accuracy of new reports
adoption rate of new tools/processes
minimal post-implementation issues
designs are scalable and maintainable.

Stakeholder Confidence & Influence

Your ability to be seen as the trusted expert and go-to person for complex performance queries, influencing decisions on data architecture and reporting strategy.

Portfolio Managers proactively seek your advice on new product launches
you're invited to strategic IT/Data governance meetings
positive feedback from managers on your ability to communicate complex issues clearly and persuasively.

Team Mentorship & Development

Your effectiveness in guiding, coaching, and developing junior members of the performance team.

Junior analysts consistently meet their development goals
positive feedback from mentees on your support and guidance
successful onboarding of new team members
demonstrable improvement in team's technical capabilities.

Technical Leadership & Innovation

Your contribution to advancing the team's technical capabilities, introducing new methodologies, or championing better tools and practices.

Successful introduction of new analytical techniques (e.g., advanced attribution models)
implementation of new scripting for automation
active participation in technical communities of practice
suggestions for system improvements that are adopted.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy

Solving Complex Puzzles

You'll spend a significant chunk of your time unravelling intricate data discrepancies, designing new models for tricky asset classes, or figuring out why a vendor system is behaving unexpectedly. It's a constant intellectual challenge.

Successfully designing and implementing a new multi-currency attribution model for our global equity portfolios, which was previously a manual and error-prone process.

Building and Improving Systems

You're not just a user; you're a builder. You'll get to design new reporting frameworks, automate manual processes, and influence the technology roadmap for performance measurement, leaving a lasting impact on how we operate.

Leading the project to automate the daily reconciliation of benchmark data, reducing manual effort by 80% and improving accuracy.

Mentoring and Developing Others

You'll be directly responsible for guiding junior analysts, sharing your expertise, and helping them navigate complex technical and business challenges. Seeing them grow and succeed under your guidance is a core part of the role.

Coaching a junior analyst through their first GIPS verification project, ensuring they understand the standards and can confidently present their findings.

What frustrates people

The Upstream Data Mess: Spending a good chunk of your week cleaning and correcting data from other departments or vendors (e.g., incorrect security classifications, missing corporate actions, bad price feeds) before you can even start your actual analysis. You're now designing solutions to prevent this, but it's still a battle.
Last-Minute PM Requests: The Portfolio Manager who needs a custom, non-standard report for a client meeting in one hour, derailing your entire month-end workflow. You're the one who has to manage expectations or find a clever, quick solution.
The 'Black Box' Vendor System: When your performance system produces a number you can't explain, and the vendor's support can't give you a clear answer on the calculation logic. You're expected to figure it out.
Defending Your Numbers: Being implicitly challenged by portfolio managers when attribution results are negative, as if a bad number must be a calculation error, requiring you to meticulously explain the methodology.
The Monotony of the Close (still): While you're leading it, the repetitive, high-pressure grind of the first three business days of every month, running and validating reports under a tight deadline, is still a reality.
Retroactive Changes: Being told to change a portfolio's benchmark or historical composition, forcing a complete and painful recalculation and restatement of past performance across multiple systems and reports.

What this role does not give you

A purely strategic, 'hands-off' role: You'll still be very much in the weeds, solving complex technical problems and ensuring data integrity.
A 9-to-5, predictable schedule: Month-end and project deadlines will mean some longer hours, and urgent requests are a given.
Complete control over data inputs: You'll always be reliant on data from other teams and external vendors, which means dealing with imperfections.

8Who you work with

This role directly impacts the firm's ability to accurately represent its investment performance, which is fundamental to client trust, regulatory compliance, and attracting new business. You're building the infrastructure that underpins our investment narrative and ensures we're making data-driven decisions. Your work directly influences how we present ourselves to the market and how our portfolio managers understand their own strategies.

Inside the business

Performance Measurement Manager
Portfolio Managers (Equity, Fixed Income, Multi-Asset)
Risk Management Team
IT & Data Engineering Teams
Compliance Department
Fund Accountants

Outside the business

External GIPS Verifiers
External Auditors
Key Institutional Clients (occasionally)

9What you need before you start

Not a wish list. The things you would be expected to already have.

Proven track record of 5-8 years as a Senior Performance Analyst (or equivalent) in an asset management firm, demonstrating strong independent work and problem-solving.
Hands-on experience leading at least two significant projects related to performance measurement (e.g., new system implementation, GIPS verification, new asset class integration).
Demonstrable experience mentoring junior team members, including formal or informal coaching and technical guidance.
Advanced proficiency in Excel (VBA, Power Query) and SQL, with a portfolio of complex models or queries you've built.
Deep understanding of GIPS standards and practical experience with their application in a real-world setting.
Ability to communicate complex quantitative concepts effectively to both technical and non-technical audiences.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Statistical Modelling & Machine Learning

Beyond standard risk-adjusted metrics, we'll be looking to incorporate more sophisticated statistical techniques for factor analysis, predictive performance, and identifying non-linear relationships in returns. This will help us provide deeper insights into portfolio behaviour.

Factor analysis and regression models · Time series analysis for performance forecasting · Clustering and classification for portfolio segmentation · Model interpretability (XAI)

This week: Read up on common statistical models used in quantitative finance.
This month: Complete an online course on Python for data science, focusing on scikit-learn and statsmodels.
Month 2: Propose a pilot project to apply a simple regression model to explain the performance of one of our equity portfolios.
Month 3: Present your findings and the potential benefits of these techniques to the wider team and Portfolio Managers.

Quick win: Start experimenting with Python libraries like `statsmodels` or `scikit-learn` on historical performance data. Even basic linear regression can yield interesting insights.

Data Virtualisation & API Integration

To provide more flexible and real-time access to performance data, we'll move towards data virtualisation layers and robust API integrations. This means less reliance on static reports and more on dynamic, on-demand data access for internal and external users.

API design principles (RESTful) · Data virtualisation concepts · Microservices architecture · Security and authentication for data access

This week: Research common data virtualisation platforms and API gateway technologies.
This month: Work with our IT team to understand our current API strategy and how performance data could be exposed.
Month 2: Design a conceptual API for a specific performance data set, outlining endpoints and data structures.
Month 3: Participate in a project to integrate a new data source via API, gaining hands-on experience.

Quick win: Familiarise yourself with how our existing market data APIs (Bloomberg BQL, FactSet FQL) work and consider how you might design a similar internal API for performance data.

11Staying current once you are in

What people here do to keep up

Regularly attend industry conferences and webinars focused on investment performance, GIPS, and financial data analytics. Stay current with the latest thinking.
Actively participate in professional associations like the CFA Institute or local performance measurement groups. Networking and sharing best practices are key.
Pursue advanced training in Python for data science, especially focusing on libraries relevant to financial modelling and automation.
Take courses or certifications in cloud data platforms (e.g., AWS, Azure, GCP) to understand modern data architecture principles.
Engage in internal cross-functional projects that expose you to different areas of the business, like risk management or product development.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration

Frankly, competitors are already using tools like GPT and Claude to draft reports in minutes that used to take hours. Analysts who figure this out will outproduce peers significantly. This isn't future-gazing; it's happening now.

Context windows and token limits
Temperature settings for different tasks
RAG (Retrieval Augmented Generation) architectures
Output validation and hallucination detection
Prompt chaining for complex analysis

Cloud-Native Data Platforms (e.g., Snowflake, Databricks)

As our data volumes explode and the need for real-time analytics grows, traditional on-premise databases just can't keep up. Cloud platforms offer scalability and flexibility that will become essential for our performance data architecture.

Cloud data warehousing principles
ELT (Extract, Load, Transform) pipelines
Data governance in the cloud
Cost optimisation strategies

13What you’ll use

What you’ll use

Skills this role draws on

Technical

GIPS (Global Investment Performance Standards)
Performance Attribution Analysis
Risk-Adjusted Performance Metrics
Return Calculation Methodologies
Fixed Income Analytics & Attribution
Data Reconciliation & Governance

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

1
Senior Performance Analyst (L3)
3-5 years as a Senior Analyst
Skills to master
- Deep expertise in a specific asset class, leading smaller projects independently, effective mentorship of junior colleagues, and a solid understanding of GIPS application. You'd be the go-to person for complex calculations.
You're ready to move on when
- Consistently delivering complex performance reports with minimal supervision.
- Successfully led at least one major internal project (e.g., new report build, process automation).
- Received strong feedback on your ability to mentor and guide junior team members.
- Proactively identified and resolved systemic data issues, not just individual errors.
2
Data Analyst (Finance)
5-8 years in a data-focused role within finance
Skills to master
- Strong SQL and Python skills, experience with large financial datasets, a good understanding of investment products, and a keen eye for data quality. You'd need to pick up the specific performance methodologies quickly.
You're ready to move on when
- Demonstrated ability to build complex data pipelines and analytical solutions.
- Experience working with financial market data and understanding its nuances.
- Proven ability to translate business requirements into technical data solutions.
- A genuine interest in investment performance and a willingness to learn the domain specifics.
3
Investment Risk Analyst
4-7 years in investment risk management
Skills to master
- Deep understanding of risk metrics (e.g., VaR, tracking error), portfolio construction, and quantitative analysis. You'd need to bridge your risk knowledge with performance attribution and GIPS.
You're ready to move on when
- Strong analytical and quantitative skills, with experience in statistical modelling.
- Familiarity with various asset classes and their risk characteristics.
- Ability to communicate complex risk concepts to Portfolio Managers.
- A desire to focus more on the 'why' behind performance and less on pure risk measurement.

15Where this role leads

The long view: This role can lead to managing larger teams, working as a deep technical specialist, or shaping data strategy across a firm.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Lead Performance Analyst is actually changing.

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Analytics, worked against Lead Performance Analyst.

Data Analytics Level 5

Applied to your work in Lead Performance Analyst

The objective of this unit is to enable learners to understand and apply data analytics techniques for decision-making. Learners will be able to apply descriptive, predictive, and prescriptive analytic methods, utilising statistical methods, to convert raw data into actionable insights and determine the best course of action.

How the thinking builds

1 Remember
2 Understand
3 Apply
4 Analyse
5 Evaluate
6 Create

An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Lead Performance Analyst plan, free

See Your Progress Grow Illustration

Lead Performance Analyst

GIPS (Global Investment Performance Standards)
Performance Attribution Analysis
Risk-Adjusted Performance Metrics
Return Calculation Methodologies
Fixed Income Analytics & Attribution
Data Reconciliation & Governance

This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Lead Performance Analyst is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

Performance Measurement Manager (L5)
3-5 years as a Lead Performance Analyst

You'd move from leading projects and a small team to managing the entire performance measurement function. This means full accountability for all reporting, managing a larger team (including other Leads), and setting departmental strategy.
- Organisational design and workflow optimisation for a multi-team structure.
- Vendor relationship management for core performance systems.
- Risk management and audit oversight for the entire function.
- Representing the firm externally on performance-related matters (e.g., industry panels).
Quantitative Analyst / Research Specialist
3-6 years as a Lead Performance Analyst

This is an Individual Contributor (IC) path, moving into a role focused purely on advanced quantitative analysis, model development, and research. You'd apply your deep understanding of performance and risk to build new analytical tools for the investment team.
- Building and backtesting quantitative investment strategies.
- Developing proprietary risk and attribution models.
- Programming in languages like Python or R for advanced analytics.
- Working with large, unstructured financial datasets.

Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a big chunk of a Lead Performance Analyst's job can feel like a grind: sifting through data, drafting commentary, chasing down anomalies. But here's the thing: AI isn't here to replace you; it's here to make you incredibly more productive. Imagine offloading the tedious, repetitive stuff so you can focus on the truly strategic work – the stuff that actually moves the needle for our investment performance.

We're investing in AI tools to supercharge our Finance_roles team. For a Lead Performance Analyst, this means using intelligent assistants to automate reconciliations, draft initial performance commentaries, and even help investigate those stubborn data outliers. Think of it as having a highly efficient co-pilot for your most time-consuming tasks. We're not just talking about theory; we're talking about practical, daily applications that will give you back hours every week.

Automated Reconciliation Agent

Imagine an AI tool that automatically ingests custodian statements, broker files, and our internal accounting data. It performs a multi-way reconciliation, flagging specific discrepancies (like dividend mismatches or trade settlement errors) and even suggesting likely causes. As a Lead, you'll be designing the rules for this agent and validating its outputs, not manually crunching numbers.

Insightful Commentary Drafter

A Natural Language Generation (NLG) model that analyses your attribution output data and automatically generates a first draft of performance commentary. It highlights the top positive/negative contributors, explains the impact of asset allocation vs. security selection, and summarises key trends. You'll be refining, not writing from scratch, saving hours on repetitive writing tasks.

Anomaly Investigation Assistant

When a performance outlier is detected, this AI tool scans market data feeds, news APIs, and internal trading logs related to the specific security or sector. It provides a concise summary of potential causes (e.g., 'Company X reported earnings miss,' 'Central bank announced rate hike'). You'll get a head start on your root cause analysis, letting you focus on the deeper 'why'.

GIPS Compliance Co-Pilot

An AI-powered documentation tool that helps you prepare for GIPS audits. It can scan policies and report disclosures, flagging potential inconsistencies with GIPS standards. It also helps organise and retrieve evidence (e.g., 'Show me all composites that included Portfolio XYZ in Q3'). This means less frantic searching and more confident audit preparation.

Common questions

How do you become a Lead Performance Analyst?

Common routes in include Senior Performance Analyst (3-5 years as a Senior Analyst), Data Analyst (Finance) (5-8 years in a data-focused role within finance) and Investment Risk Analyst (4-7 years in investment risk management). Times vary with prior experience.

Where can a Lead Performance Analyst progress to?

This role can lead on to Performance Measurement Manager (3-5 years as a Lead Performance Analyst) and Quantitative Analyst / Research Specialist (3-6 years as a Lead Performance Analyst), depending on the skills you build.

What new skills matter most for a Lead Performance Analyst?

Increasingly, Prompt Engineering & LLM Integration and Cloud-Native Data Platforms (e.g., Snowflake, Databricks). These are the skills our record of this role lists as growing.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Lead Performance Analyst plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.

Lead Performance Analyst

Where should we send it?

Two short quizzes about you

Will AI change your work as a Lead Performance Analyst?

What's rising in its place

Prompt Engineering & LLM Integration

Cloud-Native Data Platforms (e.g., Snowflake, Databricks)

Skills this role draws on

Technical

How you actually get there, here

Senior Performance Analyst (L3)

Data Analyst (Finance)

Investment Risk Analyst

The credential is what you can do today. These are what keep you valuable.

Roles this leads to

One to one, on the work you already do

Everything else the record holds

The career path, and where it branches

Performance Measurement Manager (L5)

Quantitative Analyst / Research Specialist

Where AI is starting to help

Automated Reconciliation Agent

Insightful Commentary Drafter

Anomaly Investigation Assistant

GIPS Compliance Co-Pilot

Common questions

Want a read on where you stand?