Associate – Private Credit (SME Lending)

Cobalt Recruitment; Greater London; On-site; GBP 40,000 - 60,000; Full time

Job summary

A specialist private credit fund in London is seeking a technically strong Associate to join its investment team. The candidate will have a direct impact on investment decisions through robust financial modelling and analysis across multiple asset classes. This challenging role demands strong analytical skills and the ability to work independently, as there are no rigid templates. Candidates with 2–5 years of experience in private credit or related fields will thrive. The environment promotes intellectual curiosity and offers immediate responsibilities.

Qualifications

• 2–5 years’ experience in private credit, structured or specialty finance, or asset-backed lending.
• Ability to build complex Excel models from scratch.
• Exposure to multiple credit types is highly desirable.

Responsibilities

• Analyse borrower financials and loan datasets.
• Build bespoke Excel models for credit risk assessment.
• Challenge borrower assumptions and assess underwriting methodologies.

Skills

Strong analytical thinking

Complex Excel modelling

Handling large datasets

Credit risk assessment

Job description

A fast-growing, London-based specialist private credit fund is seeking a technically strong Associate to join its investment team.

The business deploys capital across SME cashflow lending, asset-backed finance, real estate, forward flow, and platform lending strategies.

This is not a traditional institutional environment. There are no rigid templates or predefined underwriting models—every deal requires independent thinking, bespoke modelling, and genuine credit judgement.

You will join a small, high-performing team where your analysis directly influences investment decisions from day one.

What Makes This Role Different

• Direct exposure to senior decision-makers within a lean team
• Immediate responsibility for financial modelling and analysis
• Exposure across multiple asset classes

Strong analytical thinking is recognised. Weak analysis is challenged.

Key Responsibilities

• Analyse borrower financials and large, unstructured loan datasets
• Build bespoke Excel models from first principles to assess credit risk
• Identify inconsistencies and challenge borrower assumptions
• Construct default curves, vintage analysis, and roll-rate matrices
• Model SME cashflows, covenant headroom, and downside scenarios
• Assess underwriting methodologies of lending platforms
• Evaluate probability of default using quantitative and qualitative factors
• Translate complex analysis into clear credit recommendations
• Engage with origination channels (e.g. brokers) to support deal flow
• Support relationship management and post-investment monitoring

Technical Requirements

This role requires strong modelling capability and intellectual curiosity around risk:

• Ability to build complex Excel models from a blank workbook
• Experience handling large datasets (20k+ rows)
• Knowledge of vintage, cumulative default, and roll-rate analysis
• Ability to reconcile inconsistencies in borrower data
• Flexibility to apply different analytical frameworks across asset classes
• Advanced Excel skills (Pivot Tables, XLOOKUP/INDEX-MATCH, SUMIFS, dynamic modelling)

Ideal Background

2–5 years’ experience in one or more of the following:

• Private credit
• Structured or specialty finance
• Asset-backed lending
• Structured products

Exposure to multiple credit types is highly desirable.

• Analytical and performance-driven
• Entrepreneurial rather than institutional
• Flat structure with high ownership

You will work closely with senior team members and develop practical credit judgement across a broad range of transactions.

Who Will Thrive

This role suits someone who:

• Enjoys building rather than operating processes
• Is intellectually curious about credit risk
• Is comfortable making decisions with imperfect data
• Thinks independently rather than relying on templates
• Can move between consumer-style portfolio modelling and SME underwriting
• Has strong commercial awareness (not purely academic)