Fraud Analytics Analyst II (SQL & Python)

TD

Ottawa

On-site

CAD 82,000 - 115,000

Full time

36 hours ago
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Job summary

TD in Ottawa is seeking an Analytics Fraud Performance professional to mine big data, derive actionable fraud insights, and shape strategies in a fast-paced environment. You would manage evolving fraud threats with a strong technical and analytics background.

You will work with TD risk, Customer and operations teams to balance loss with customer experience, deploying fraud strategies and monitoring across channels.

Qualifications

  • Undergraduate degree in a technical field (CS, engineering, math or stats).
  • 2+ years of hands-on analytics experience.
  • Advanced SQL and Python for data analysis.
  • Knowledge of data science tools such as NumPy, pandas, matplotlib (or R).
  • Ability to communicate analyses to technical and non-technical audiences.
  • Proactive, able to manage multiple work streams independently.

Responsibilities

  • Develop and deploy fraud strategies to reduce fraud risk while balancing loss, customer experience and operational capacity.
  • Identify new fraud vectors and optimize existing rules using SQL, Python and fraud authentication solutions.
  • Conduct intra-day and weekly monitoring across products, channels and risk segments.
  • Provide ad-hoc analyses to support executive decision-making.
  • Continually optimize and strengthen fraud analytics capabilities and strategies.
  • Independently investigate new high-risk fraud threats under tight timelines.

Skills

SQL
Python
Fraud analytics
Data mining
Communication

Education

Undergraduate degree in a technical field

Tools

NumPy
pandas
matplotlib
fraud authentication solutions

Job description

TD in Ottawa is seeking an Analytics Fraud Performance professional to mine big data, derive actionable fraud insights, and shape strategies in a fast-paced environment. You would manage evolving fraud threats with a strong technical and analytics background.

You will work with TD risk, Customer and operations teams to balance loss with customer experience, deploying fraud strategies and monitoring across channels.

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