Credit Risk Analytics Consultant

Aspire Data Recruitment
London
3 months ago
Applications closed

Related Jobs

View all jobs

POWERCURVE CONSULTANT

POWERCURVE CONSULTANT

Experian Powercurve Consultant

Principal Data Science Consultant - Financial Services Expertise (Basé à London)

e-Discovery Manager

eDiscovery Project Managers (all levels)

Credit Risk Analytics Consultant
London or Birmingham, to £70,000 plus bonus and benefits

As part of a team, you’ll be involved in designing, developing, and deploying state-of-the-art, data-driven predictive models to solve business problems using the latest technologies in data mining, statistical modeling, pattern recognition, and performance inference.

The Role

  • Design and develop state-of-the-art, data-driven exploratory analysis as well as predictive and decision models to solve business problems.
  • Build and evaluate predictive and decision models to be deployed in production systems, or for research. This includes the analysis of large amounts of historical data, determining suitability for modelling, data clean-up, pattern identification and variable creation, selection of sampling criteria and performance definition, and variable selection.
  • Experiment with different types of algorithms and models, analysing performance to identify the best algorithms to employ.
  • Assist with technical product support for new or existing products/services; this includes, but is not limited to, production of sales collateral or ad-hoc investigations initiated by internal or external clients. Work simultaneously on multiple projects of moderate size and complexity.
  • Plan effectively to set priorities and manage projects, identify roadblocks and work to get them removed, and understand the importance of meeting deadlines.
  • Handle communication with internal and external clients as needed.
  • Determine appropriate model report format for communication with clients.
  • Participate in authoring white papers, proposals and publications.
  • Mentor other scientists and assign modelling tasks when appropriate.

Background

  • A graduate, ideally with a mathematical or statistical degree (or a degree with a high level of quantitative, statistical or operational research content) or relevant experience.
  • Experience with an analytic solutions or consulting company, and preferably in a client-facing project management capacity.
  • Knowledge and experience in applying data to solve business problems through quantitative analysis, experience with predictive modelling and optimisation, and knowledge of the principles and practices of project management.
  • Experience with credit risk model developments. Experience with fraud and marketing analytics a plus.
  • Strong statistical, data processing and analytical skills.
  • An excellent communicator with the ability to explain complex concepts and describe technical material to non-technical users.
  • Knowledge of scoring technology and methodologies; model development techniques and tools; advanced statistical methods and quantitative analysis; statistical tools and programs; fluency in SAS, WPL, R, Python or other similar programming language.


Please send your CV or call us on 01706 825 199.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Contract vs Permanent Data Science Jobs: Which Pays Better in 2025?

Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.