Senior Data Scientist

Vanguard; City of Westminster; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading investment company in the City of Westminster is seeking a skilled Machine Learning Engineer to develop and deploy machine learning models to address business challenges in finance. The ideal candidate will possess a master's or PhD in a related field and have proven experience in advanced analytics, with demonstrated expertise in Python and R. Strong communication skills are essential for articulating complex concepts to non-technical stakeholders. This role embraces a hybrid working model, promoting flexibility and collaboration.

Benefits

Hybrid working model

Mentoring opportunities

Qualifications

• Proven hands-on experience in advanced analytics or data science.
• Expertise in deploying ML models with business impact.
• Exceptional communication skills to present complex data concepts.

Responsibilities

• Develop and deploy machine learning models for business challenges.
• Partner with teams to translate requirements into technical specifications.
• Optimise AI/ML workflows for scalability and reliability.

Skills

Machine learning

Python

R

NLP

Statistical modeling

Cloud platforms

Data engineering

Communication

Education

Master’s or PhD in relevant field

Tools

Scikit-learn

PyTorch

Keras

SQL

Spark

AWS

Azure

GCP

Docker

Kubernetes

Job description

Core Responsibilities

• Develop and deploy machine learning models (e.g., time‑series forecasting, NLP pipelines, generative AI tools) to solve specific business challenges in finance, such as risk modelling, portfolio optimisation, or client personalisation
• Partner with cross‑functional teams to identify business needs, translate requirements into technical specifications, and validate model performance in production environments
• Optimise existing AI/ML workflows for scalability, efficiency, and reliability using frameworks like PyTorch, TensorFlow, or cloud‑based infrastructure
• Collaborate with research scientists to adapt cutting‑edge algorithms (e.g., LLM fine‑tuning, reinforcement learning) into actionable business solutions
• Document and maintain codebases, ensuring reproducibility, version control, and alignment with industry best practices (e.g., CI/CD pipelines)
• Mentor junior team members and educate stakeholders on AI/ML capabilities, limitations, and ethical considerations

Education & Qualifications

• Education: Master’s or PhD in Computer Science, Statistics, Mathematics, Analytics, Economics, or a closely related field. (Graduate degree strongly preferred; equivalent advanced training and experience considered.)
• Experience: Proven hands‑on experience in advanced analytics, applied data science, or machine learning engineering, with a proven track record in the financial services industry or similar complex domains.
• Technical Mastery: Demonstrated expert proficiency in Python and R, including hands‑on experience with leading ML frameworks (Scikit‑learn, PyTorch, Keras), data engineering tools (SQL, Spark), and cloud platforms (AWS, Azure, GCP). Deep experience in applied mathematics, statistical modeling, machine learning, and AI applications.
• Production Impact: Successfully deployed multiple ML models to production environments, with direct business impact (e.g., measurable improvements in KPIs, cost savings, or risk reduction). Experience with containerisation (Docker, Kubernetes), CI/CD, SDLC, and MLOps/observability practices.
• Advanced Methods: Expertise in NLP, deep learning, transformer‑based models, and generative AI. Proven ability to define and track value metrics, run experimentation (A/B testing, causal inference), and drive stakeholder adoption from MVP through scale.
• Domain Knowledge: Familiarity with financial domains such as asset management and risk analytics, with a history of delivering quantifiable business outcomes (e.g., increased revenue, reduced risk, improved operational efficiency).
• Communication & Influence: Exceptional verbal and written communication skills, with the ability to articulate complex data science concepts and technical results to non‑technical stakeholders and senior leadership. Experience leading cross‑functional teams and driving adoption of analytics solutions.
• Leadership: Demonstrated success in mentoring and developing junior talent, leading organisation‑wide training initiatives, and fostering a culture of innovation and collaboration.

About Vanguard

Vanguard is a different kind of investment company. It was founded in the United States in 1975 on a simple but revolutionary idea: that an investment company should manage its funds solely in the interests of its clients. This is a philosophy that has helped millions of people around the world to achieve their goals with low‑cost, uncomplicated investments. It is what we stand for: value to investors.

Inclusion Statement

Vanguard's continued commitment to diversity and inclusion is firmly rooted in its culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: "Do the right thing." We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard's core purpose through its values. When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

Our commitment to equal employment opportunity

Vanguard is an equal‑opportunity employer. Vanguard is committed to providing all crew members a working environment that is free from discrimination, prejudice and bias. Through this Equal Employment Opportunity (EEO) Policy, Vanguard reaffirms its commitment to equal employment opportunity for all applicants and crew members without regard to race, colour, national origin or ancestry, religion, gender, sex, sexual orientation, gender identity or expression, age, disability, marital status, veteran or military status. In addition, Vanguard prohibits discrimination based on genetic information, as well as any other characteristic protected by federal, state or local law. Applicants with disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Vanguard. Please inform [e-mail] if you need assistance completing this application or to otherwise participate in the application process.

How We Work

Vanguard has implemented a hybrid working model for the majority of its crew members, designed to capture the benefits of enhanced flexibility while enabling in‑person learning, collaboration, and connection. We believe our mission‑driven and highly collaborative culture is a critical enabler to support long‑term client outcomes and enrich the employee experience.