Vice President, Data Management & Quantitative Analysis

BNY
Manchester
2 weeks ago
Applications closed

Related Jobs

View all jobs

Assistant Vice President Compliance Data Governance

Markets Operations - Data Governance Program Management Lead - Vice President

Markets Operations - Data Governance Program Management Lead - Vice President

Markets Operations - Data Governance Program Management Lead - Vice President

Markets Operations - Data Governance Program Management Lead - Vice President

Markets Operations - Data Governance Program Management Lead - Vice President

Vice President, Data Management & Quantitative Analysis

Join to apply for the Vice President, Data Management & Quantitative Analysis role at BNY.


At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting‑edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.


We’re seeking a future team member for the role of Vice President, Data Management & Quantitative Analysis to join our Data and Quantitative Analysis team. This role location is based in Manchester, UK.


Responsibilities

  • Lead the development and implementation of data management strategies by leveraging expertise in data analysis and quantitative methodologies.
  • Ensure data integrity and accuracy across all platforms by establishing rigorous data governance frameworks and protocols.
  • Collaborate with cross‑functional teams to translate complex data insights into actionable business strategies, enhancing decision‑making processes.
  • Drive continuous improvement initiatives in data management practices by staying abreast of industry trends and emerging technologies.
  • Mentor and guide junior team members, fostering a culture of learning and development within the data management team.
  • Champion data‑driven innovation by identifying opportunities for automation and efficiency enhancements in data processing and analysis.

Qualifications

  • Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field. Advanced degree preferred.
  • Strong analytical and quantitative skills, with the ability to interpret complex datasets and deliver actionable insights.
  • Excellent communication skills, capable of conveying technical concepts to non‑technical stakeholders.
  • Proficient in data management tools and platforms, with a continuous improvement mindset.
  • Prior experience in risk and regulatory reporting, with a strong understanding of associated frameworks and compliance requirements, is highly desirable.

Benefits and Rewards

BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay‑for‑performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.


BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.


#J-18808-Ljbffr

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.

Jobs

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Education Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.