Data Analyst with experience in AWS serverless data platforms, data migration, and analytics/model development. Skilled in SQL, Python, AWS, Snowflake, Databricks, Power BI, Tableau, and machine learning techniques inclu…
Data Analyst with experience in AWS serverless data platforms, data migration, and analytics/model development. Skilled in SQL, Python, AWS, Snowflake, Databricks, Power BI, Tableau, and machine learning techniques including regression, NLP, and neural networks. Currently Data Analyst at Sun Life Global Investments (Aug 2025–Present), building AWS-based data platforms for investment operations; previously Data Analyst at RBC Insurance (May–Dec 2023), where I redeveloped a predictive retention model reaching 91.6% accuracy and contributing $1.13M in incremental sales. Master of Information (Human-Centred Data Science), University of Toronto, 2024. Seeking remote part-time/contract work, about 10–15 hours per week with flexible scheduling, alongside full-time employment.
<p>Designed and built the AWS serverless data platform behind a firm-wide fund-accounting provider migration, consolidating fragmented vendor API and SFTP feeds into shared staging tables that ingest 34M+ records a year for fund accounting, performance, custody and pricing.</p><p> Engineered a configuration-driven orchestration layer that gates 16 Glue jobs on source-file readiness, with an arrival watchdog, automatic quarantine, full lineage and single-date replay; validated in parallel against legacy output and cut over in three tranches with zero material incidents.</p><p> Owned an advisor intake automation for Portfolio Management end to end, replacing manual reconciliation and re-keying with a live 23,884-instrument reference list, automated Glue validation, form population and SFTP delivery; cut per-submission handling by over 90% (60–90 min to 5), saving ~$110,000 annually; presented to a VP.</p><p> Led the program-wide decommissioning of 126 legacy jobs and workflows while in-housing an offshore-managed platform, coordinating five teams including Mainframe Operations and securing formal sign-off from Risk Management and Compliance; authored the documentation standard adopted program-wide.</p><p> Rebuilt four legacy Informatica/mainframe processes on AWS, cutting a daily Charles River feed's runtime by ~70% (3–4 hours to ~1) across 17 tables of ~10M rows via a server-side SQL MERGE skipping unchanged rows.</p>
<p>Led end-to-end migration and redevelopment on a predictive model for Future Income Options (FIO) with an engineered Customer Loyalty metirc; boosted retention forecasting accuracy to a record high of 91.6%, and directly contributed to $1.13M in incremental sales revenue for fiscal 2023.<br>
Supported the development of a Term-100 life insurance propensity model by conducting multi-granular customer behavior analysis across 8+ million records spanning 40 years using DB2 SQL and Python; insights from this analysis played a key role in downstream customer segmentation and strategy initiatives.</p>
<p>Collaborated with team members to conduct student education status-related data mining from Government reports and organization-issued assessments.<br>
Delivered structured datasets and analysis that contributed to published research insights on Ontario education system disparities.</p>
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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