Senior Assistant Vice President - Data Strategy

Job Title : Senior AVP, Data Strategy

Skills :

- Python

- Libraries like matplotlib, plotly, and seaborn

About the Role :

We are seeking a highly skilled and experienced Senior Assistant Vice President (Senior AVP) to lead and execute our Data Strategy. This role sits at the intersection of quantitative analytics, risk management, and advanced technology.

You will be responsible for leveraging complex statistical theory, sophisticated programming, and financial acumen to design and implement data-driven solutions, forecast risks, and provide strategic insights that drive business initiatives. The ideal candidate is a proactive leader who can navigate complexity, manage critical projects, and collaborate effectively across technical and business teams.

Key Responsibilities :

- Design, implement, and document highly complex quantitative models and data strategies to manage market, credit, and operational risk.

- Forecast potential losses and compute capital requirements, providing actionable insights to support strategic business decisions.

- Apply advanced statistical theory to quantify, analyze, and interpret market and financial data, including structured securities.

- Lead discussions on analytical methodologies, modeling approaches, and forecasting techniques.

- Develop and maintain a robust control framework for data, solutions, and procedures, identifying and mitigating risks proactively.

- Perform root-cause analysis and remediation of data issues using Java and Python.

- Design and develop automated solutions and prototypes to address business inefficiencies and complex problems.

- Manage end-to-end process improvement initiatives to enhance operational effectiveness.

- Partner with Technology teams to enhance and debug enterprise-scale valuation, risk, and market data platforms.

- Integrate diverse data inputs into pricing and risk analytics libraries in collaboration with quantitative teams.

- Deliver high-quality software and documentation within an Agile development lifecycle.

- Effectively collaborate with technical and non-technical stakeholders, including auditors and regulators.

Required Qualifications :

- 4+ years of experience in Quantitative Analytics, Data Science, or a related field, demonstrated through work experience, training, military service, or education.

- Master's degree or higher in a quantitative discipline (e.g., Mathematics, Statistics, Engineering, Physics, Economics, Computer Science, Finance).

Desired Qualifications & Skills :

Technical Expertise :

- Advanced proficiency in Python (NumPy, Pandas, SciPy, Scikit-learn) and Java (Functional Programming, Lambda expressions, Spring Boot).

- Experience with Object-Oriented Programming, data classes, decorators, error handling, and logging.

- Strong skills in data transformation, wrangling, and analysis using Pandas (grouping, aggregation, pivoting).

- Experience with data visualization libraries (Matplotlib, Seaborn, Plotly).

- Hands-on experience with Git and version control.

- Familiarity with data sources including SQL/NoSQL databases, Hadoop/HDFS, and remote file systems.

- Experience building dashboards using frameworks like Streamlit, Dash, Django, or Flask.

- Knowledge of CI/CD tools (Jenkins, Docker, Kubernetes).

Analytical & Functional Skills :

- Proven ability to apply quantitative techniques to solve complex business and risk management problems.

- Strong analytical and critical thinking skills with a keen attention to detail.

- Experience in financial services, risk modeling, or a strong desire to learn complex financial concepts.

- Ability to lead a project from inception to delivery in an Agile environment.

- Experience developing or working with enterprise-scale software platforms.

Professional Attributes :

- Excellent communication skills with the ability to convey complex ideas to diverse audiences.

- Proactive mindset with a focus on identifying opportunities for improvement and implementing change.

- Strong collaboration and partnership skills, with the ability to work effectively across all organizational levels.

- Commitment to high-quality work, adherence to compliance requirements, and robust documentation.

Job Expectations :

- Utilize a blend of quantitative, technological, and financial expertise to address critical business challenges.

- Maintain a deep understanding of data policies, procedures, and compliance requirements.

- Consistently deliver robust, scalable, and well-documented solutions.

- Stay current with emerging technologies and methodologies in data science and quantitative finance.