TD Securities (2016–Present)

TD Securities (2016–Present)#

Technology Leader | Data Platform & Analytics | Data Strategy | Data Science Evangelism

Progressive technical and leadership roles driving innovation in data platforms, analytics, and cloud migration with a top global investment bank. Combines deep technical expertise with strategic vision to deliver scalable solutions for the business. Recognized with top-tier awards for transformational contributions.

Director, Data Platform & Analytics (2023–Present)#

I lead and oversee four critical teams that drive data excellence across the organization. My responsibilities include strategic alignment, cross-team collaboration, and ensuring high-quality deliverables while fostering innovation and governance best practices:

  1. Market Data Masters

    • Focuses on acquiring, managing, and optimizing financial market data (e.g., pricing, reference rates, trading volumes).

    • Ensures data accuracy, latency efficiency, and integration with downstream systems.

    • Works closely with traders, quants, and analytics teams to support real-time decision-making.

  2. Reference Data Masters

    • Manages static and semi-static reference data (e.g., securities master, counterparties, corporate actions).

    • Maintains golden sources of truth for critical business operations (risk reporting, compliance).

    • Collaborates with front/middle office to streamline workflows impacted by reference data changes.

  3. Data Quality & Governance

    • Establishes frameworks/metrics for data integrity, lineage tracking, and compliance.

    • Implements proactive monitoring/remediation pipelines to reduce “data fires.”

    • Partners with Legal & Risk teams to enforce policies while enabling agile use cases.

  4. Data Science Engineering

    • Provides scalable infrastructure/platforms (Jupyter Notebooks, ML pipelines) for broad quantitative analytics, reporting, AI, and upskilling.

    • Bridges gaps between research prototypes (Python/R) and production-grade deployments.

    • Supports AI/ML initiatives with clean datasets while ensuring reproducibility/monitoring.

Strategic Leadership:#

  • Define and execute platform roadmap aligned with C-suite objectives; secure buy-in from business stakeholders (trading, risk, finance).

  • Lead cross-functional teams (engineering, architecture, governance) to modernize the dealer-wide Data Platform, focusing on cloud migration (Azure/GCP), data fabric/mesh adoption, and next-gen architecture.

  • Develop and implement data governance and data quality technology strategy to provide near-realtime visibility into key data products.

  • Transform market + reference data masters platforms for more reliable, trusted golden source data, that vastly reduces manual efforts for workflows like client onboarding and data remediation.

Vice President, Data Science Engineering (2020–2023)#

Team & Stakeholder Management:

  • Built and led a high-performing engineering team supporting Python infrastructure, notebooks-as-code, and analytics tooling.

  • Acted as primary liaison between quant teams, IT security, and business units to align priorities and deliver.

  • Deliver business-enabling notebooks, applications, and processes 10-25x faster than through traditional technology processes.

  • Grow userbase organically to 1000+ users across technology, business, operations, and support teams.

Technical Innovation:

  • Scaled JupyterHub deployments via Dask-on-YARN and Spark-on-YARN integrations.

  • Architected enterprise-grade identity provider integration for JupyterHub, implementing OAuth 2.0, reducing auth-related development time while improving security posture “out of the box” to users.

  • Pioneered “EUC Governance” framework to streamline self-service analytics while mitigating operational risk.

Software Engineer Technical Lead (2019–2020)#

Technical Innovation & Platform Leadership

  • Led development of core Python libraries to provide a common interface for common data operations agnostic to the data sources (SQL, Spark, REST API) to kickstart development workflows, particularly for citizen developers

  • Designed scheduling platform for recurring jobs with, becoming critical infrastructure for prototyping and EUC processes

  • Created self-service deployment system for analytical applications that empowered business teams across front, middle, and back office to productionize dashboards without engineering support

Project Leadership:

  • Architected TDSs first centralized JupyterHub+ platform (serving 400+ users), reducing prototyping time by 70%.

  • Mentored junior engineers through code reviews and best-practice workshops (adopted org-wide).

Awards:

  • TDS Pinnacle Award of Achievement (Top 0.1% performance).

  • TD Vision In Action Award (1-in-1000 enterprise-wide recognition).

Earlier Roles#

Software Engineer (2018–2019): Bugfixes, enhacements, and early architecture for the TDS Notebooks Platform; spoke at PyCon CA (talk link).

Quantitative Developer Associate (2016–2018): Implemented derivatives pricing models; founded “Knowledge Academy” learning series (GitHub).

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