At a Glance
- Tasks: Create impactful pricing models and collaborate with teams to drive business success.
- Company: Join a leading financial services firm with a commitment to excellence.
- Benefits: Competitive pay, flexible resources, wellness programs, and generous paid leave.
- Other info: Dynamic role with opportunities for growth and innovation in data science.
- Why this job: Make a real difference in pricing strategies and enhance client relationships.
- Qualifications: Detail-oriented with strong Excel skills; experience in finance is a plus.
The predicted salary is between 80000 - 100000 £ per year.
Location: London or Manchester
Responsibilities:
- Develop commercially robust proposals that enable Client Coverage teams to win new business, and to retain and expand existing client relationships.
- Concept, build, implement & maintain pricing models, reports & dashboards.
- Work with cross-functional stakeholders to translate their analytical requirements into commercial insights.
- Collaborate with product teams to agree pricing benchmarks and guard rails.
- Support in the costing out and implementation of new services into the pricing models and fee schedules.
- Identify areas of revenue leakage.
- Work closely with revenue billing services partners and ensure invoices and fee schedules have the right components captured to avoid revenue leakage.
- Maintain good hygiene around capture of management information and KPIs.
- Lead, support and encourage initiatives to modernize BAU through AI and data science: automate repetitive tasks, implement workflow optimization, and deploy MLOps practices for reliable model lifecycle management.
Qualifications:
- High attention to detail with a desire to pursue knowledge & understanding.
- Structured approach to work.
- Advanced Excel & data visualization skills required (Power BI and/or Tableau).
- SQL experience preferred but not essential.
- Bachelor's degree or the equivalent combination of education and experience is required.
- Strong communication and negotiation skills required.
- Experience in financial accounting, economics preferred.
- Experience conducting qualitative and quantitative analysis in a business setting is preferred.
Benefits & 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.
EEO Statement:
BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.
VP, Pricing/Data/Deal Modelling & Analytics employer: BNY
At BNY, we pride ourselves on being an exceptional employer, offering a dynamic work environment in London or Manchester that fosters innovation and collaboration. Our commitment to employee growth is evident through our comprehensive benefits package, including competitive compensation, flexible resources, and generous paid leave, all designed to support your personal and professional journey. Join us to be part of a culture that values excellence and encourages you to make a meaningful impact while advancing your career.
StudySmarter Expert Advice🤫
We think this is how you could land VP, Pricing/Data/Deal Modelling & Analytics
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like BNY.
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We think you need these skills to ace VP, Pricing/Data/Deal Modelling & Analytics
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at BNY, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at BNY. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at BNY
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at BNY!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
