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Senior Associate, Data Management & Quantitative Analysis

BNY
Wrocław, województwo dolnośląskie
3 tygodnie temu

At BNY, our culture empowers you to grow and succeed. As a leading global financial services company at the center of the world’s financial system we touch nearly 20% of the world’s investible assets. Every day around the globe, our 50,000+ employees bring the power of their perspective to the table to create solutions with our clients that benefit businesses, communities and people everywhere.

We continue to be a leader in the industry, awarded as a top home for innovators and for creating an inclusive workplace. Through our unique ideas and talents, together we help make money work for the world. This is what #LifeAtBNY is all about

We’re seeking a future team member for the role of Senior Associate, Data Management& Quantitative Analysis to join our Risk Modeling team. This role is in Wroclaw (HYBRID).

Responsibilities:

  • This role will be responsible for the development, enhancement and documentation of counterparty credit risk and treasury risk modeling methodologies.
  • He/she will also assist in managing inbound questions, deliverables and ad-hoc requests with an emphasis on accuracy and timeliness of meeting deliverables on prescribed timelines.
  • Execute corporate-wide standards for model development by creating options for theoretical frameworks, collecting data needed, supporting assumptions, and reviewing outcomes.
  • Responsible for performance monitoring of models, identifying possible deterioration by comparing outcomes to established thresholds.
  • This role requires regular (written and verbal) interactions with business, technology, and other stakeholders in the bank such as Finance, Treasury, Model Risk Management.
  • Good inter-personal and negotiation skills are a key factor to accomplishing goals when interacting in a complex, multiple-priority environment. Strong programming skills in Python and R is desired.

Qualifications:

  • Strong quantitative skills: Master’s degree in a quantitative discipline, including Financial Engineering / Operations Research/ Economics / Econometrics / Statistics / Mathematics, etc. is required; PhD is a plus
  • The candidate must have experience with complex quantitative modelling, numerical analysis, and computational methods using programming languages (such as Python and R) and have experience with database.
  • Internship experience in quantitative modeling positions for a leading financial institution / central bank, consulting firm or similar
  • Experience in fixed income and equity pricing
  • Extremely focused, detail oriented and highly productive with ability to synthesize large amounts of data and various viewpoints and summarize key concepts
  • Excellent organizational and communication (verbal and written) skills
  • A proven track record of executing against deliverables and meeting deadlines under pressure
  • Works well individually and in teams, shares information, supports colleagues, and encourages participation

At BNY, our culture speaks for itself. Here’s a few of our awards:

  • America’s Most Innovative Companies, Fortune, 2024
  • World’s Most Admired Companies, Fortune 2024
  • Human Rights Campaign Foundation, Corporate Equality Index, 100% score, 2023-2024
  • Best Places to Work for Disability Inclusion, Disability: IN – 100% score, 2023-2024
  • “Most Just Companies”, Just Capital and CNBC, 2024
  • Dow Jones Sustainability Indices, Top performing company for Sustainability, 2024
  • Bloomberg’s Gender Equality Index (GEI), 2023

Our 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.

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