Asset Servicing - AVP

West End
8 months ago
Applications closed

Related Jobs

View all jobs

IPB Digital & Data Transformation -Alternative Investments Advisor & Client Experience - Produc[...]

Quantitative Developer (Low Latency) EMEA (F/M/D)

Asset Data Analyst

Asset Data Analyst

Asset Data Analyst

Asset Data Analyst

Asset Servicing - AVP working for an international Investment Manager who specialise in the Loans and Consumer Credit sphere. The office is based in London's West End, but the wider organisation has teams situated in the US and multiple European locations.

Client Details

Well known global Asset Manager who has offices in the US and Europe. They specialise in the Mortgage and Consumer Credit fund sphere. They employee circa 2000 people globally and are looking to add to their London based Asset Servicing Team in a Fund Ops capacity.

Description

This individual will play a key leadership role overseeing asset servicing and post-closing operational workflows for the European portfolio of whole loans and structured credit products. In this high-impact role, you will focus on enhancing and streamlining operational processes to improve efficiency and accuracy while maintaining synchronisation across reporting, reconciliation, and system updates. You'll collaborate with deal operations and broader finance teams based in Europe and USA ensuring accuracy of high data quality in order to optimise asset servicing and reporting processes. Strong communication skills are essential, as the individual will collaborate closely with business leaders, investment managers, transaction managers, lenders, servicers, and trustees. The successful candidate will be responsible for building new workflows, optimising existing processes, and leading a team to support evolving business needs.

Lead and oversee the end-to-end asset servicing operational workflows for portfolio of whole loans (Residential, Consumer, Commercial), including asset-based financing, securitizations and structured credit products.
Manage and oversee daily reconciliation processes with document custodians, third party servicers, trustee cash accounts and lender waterfalls.
Serve as a key resource in the deal onboarding process to oversee deal treasury workflows, ensure portfolio management systems are correctly set up with connectivity and reconciliation parameters to support asset servicing workflows.
Serve as a champion and key subject matter expert on all post-closing operational workflows related to servicing and financing transactions, driving key decisions and providing expertise to all internal teams.

Lead initiatives and work directly with investment managers and servicing oversight to produce and streamline loan level data and reporting including playing an active role in the valuation process while reviewing and reconciling the monthly NAV and P&L.

Partner with Technology, Finance and Deal Operations teams to enhance reporting capabilities and optimise data management.

Build and maintain strong relationships with third party servicers, trustees and lenders.

Lead initiatives to enhance and automate deal operations using tools such as Excel, Power BI, Arcesium, and Alteryx to improve process efficiency and support scalability.

Perform data quality checks across systems to ensure accuracy and synchronisation of key data points throughout all processes.

Proactively drive process improvements and creatively seek ways to uncover additional efficiencies.Profile

Asset Servicing - AVP

SKILLS/KNOWLEDGE/ABILITIES

Previously have held a similar Asset Servicing role, specifically within Mortgages / Consumer Credit or similar
Demonstrate sound judgement and decision-making skills, taking ownership for outcomes and delivering strong results.
Strong tech forward mind-set, proficiency in Excel, Alteryx, Power BI, SQL, Python or other management reporting tools is a strong plus.
Strong conceptual understanding of financial products and investment vehicles for whole loan investments.
Experience with residential, consumer and commercial whole loan investment workflows is a strong plus.
Strong financial acumen and analytical skills.
Strong attention to detail to ensure the accuracy of transaction level data sets.
Comfortable working with large data sets; experience analysing and reconciling deal level data.
Ability to interpret and apply analysis to complex documents and transactions.
Strong relationship management skills with the ability to interact effectively with fund managers, servicers, trustees, and senior management.
Excellent organisational and problem-solving skills, with the ability to manage multiple tasks and oversee recurring processes in a fast-paced environment.
Strong verbal and written communication skills, with the ability to collaborate across teams and departments, and effectively present to senior management.
Demonstrated ability to proactively drive process improvements and creatively seek ways to uncover additional efficiencies.

Education and Experience

An undergraduate degree in accounting, finance, or related field is required; an advanced degree or relevant certification is a plus.
Experience in operations, fund accounting, or finance, preferably within the mortgage or asset management industries.Job Offer

Asset Servicing - AVP, Fund Administration role

Industry: Financial Services, specifically Asset Management

Based: London, West End

Salary: £75-100k base plus bonus

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.