Senior Principal - Quantitative Analyst - FinTech/Financial Services/Asset Management
Company Brief (Confidential):
- Our client is a global leader in financial intelligence and investment research, serving investors, advisors, asset managers, and institutions across multiple markets worldwide.
- At the core of the organization lies a mission-critical investment data platform that collects, standardizes, validates, and enriches global fund and market data. This data powers investment analytics, performance models, ratings, and decision-support systems used by millions of professionals globally.
- The organization is currently undergoing a major data modernization and quality transformation journey, leveraging advanced statistics, AI/ML, automation, and cloud-native architectures to elevate data trust, observability, and scalability to institutional standards.
- This role is part of that transformation and sits at the heart of global investment data quality and model readiness.
About the Role:
- This is a Senior Principal quantitative leadership role responsible for ensuring the accuracy, integrity, and statistical reliability of global investment data.
- As a Senior Principal Quantitative Analyst, you will operate at the intersection of quantitative finance, applied statistics, AI/ML, and data governance, defining how data quality is measured, predicted, automated, and trusted before it feeds downstream investment models and analytics platforms.
Why This Role Is Critical:
- You will define and own quantitative data quality frameworks at global scale
- You will apply AI/ML to proactively prevent data issues, not just detect them
- You will influence data architecture, governance, and regulatory readiness
- You will work closely with quant researchers, data scientists, engineers, and senior leaders
- Your work will directly impact investment decisions, client trust, and regulatory defensibility
Key Responsibilities:
- Lead the design, implementation, and evolution of quantitative data quality frameworks, including statistical validation, anomaly detection, and drift analysis
- Build and deploy AI/ML-driven predictive quality checks to proactively identify and prevent data inconsistencies
- Apply advanced statistical techniques such as time-series analysis, regression modeling, and Bayesian inference to monitor and assess data integrity
- Collaborate with quantitative researchers, data scientists, and engineers to ensure data readiness for investment models and algorithms
- Create automated, scalable, and auditable validation pipelines with real-time monitoring and exception reporting
- Partner with stakeholders to uphold data governance, privacy, and regulatory compliance standards
- Mentor and guide junior analysts, fostering a culture of analytical rigor, innovation, and continuous improvement
- Translate complex quantitative insights into clear, actionable narratives for senior leadership and non-technical stakeholders
- Drive innovation through automation-first approaches, reproducible modeling pipelines, and ML-based data correction systems
- Contribute to the modernization of data platforms by integrating data observability, telemetry, and metadata-driven quality measures
What Were Looking For:
Core Expertise:
- Strong foundation in quantitative finance, econometrics, and applied statistics
- Deep understanding of financial instruments, fund structures, NAVs, returns, and performance analytics
- Proven experience handling large-scale structured and unstructured financial data
- Exceptional analytical thinking and statistical reasoning skills
- Ability to lead through influence in cross-functional, fast-paced environments
Technical Skills:
- Hands-on expertise in Python, R, and SQL
- Experience using AI/ML frameworks for anomaly detection and predictive modeling (e.g., scikit-learn, TensorFlow, PyTorch)
- Exposure to cloud-based data ecosystems and modern data platforms
- Strong experience with automation, data pipelines, and validation frameworks
Governance & Leadership:
- Working knowledge of data governance, lineage, auditability, and regulatory standards
- Strong communication skills with the ability to explain complex concepts to senior stakeholders
- Demonstrated mentorship and leadership maturity
Preferred Qualifications:
- Masters degree in Statistics, Mathematics, Financial Engineering, Data Science, or Quantitative Finance
- Professional certifications such as CFA, FRM, CQF, or Six Sigma Black Belt
- Prior experience in financial services, asset management, market data, or fintech environments
- Entrepreneurial mindset with a passion for innovation, scalability, and long-term impact.
What This Role Offers:
- Ownership of mission-critical investment data quality systems
- Opportunity to define global standards, not just follow them
- Exposure to cutting-edge AI/ML applications in financial data quality
- High visibility and strategic influence in a global organization
- Long-term career growth
If you are driven by analytical depth, intellectual rigor, and building data systems that markets trust, this role will challenge and reward you in equal measure.
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