Data Science Leader for Consumer Banking

1 week ago

Old Toronto, Canada Informa Connect of Informa PLC Full time

At Informa Connect, a leading business intelligence and events company of Informa PLC, we empower financial institutions to drive informed decision-making through industry-leading data, technologies, and insights.

We're operating in a hybrid modality, with the opportunity to work from our Toronto office. All candidates must possess work authorization that doesn't require sponsorship by an employer.

Job Overview

We're seeking an experienced Data Scientist to join our Data Science Team focused on applying data science, machine learning, and AI approaches to understand banking customer behavior and optimize engagement marketing through our FinTech product platforms. As a seasoned professional, you'll be passionate about finding patterns, trends, and opportunities to enhance consumer banking experiences, curious about driving KPIs and customer outcomes, and insightful in your analytical approach.

You'll bring data-driven insights into conversations about our customers, pursue improvements proactively, and build on shared cross-functional knowledge and expertise.

Key Responsibilities
  • You'll combine data sources, apply multiple data and algorithmic approaches to create a clear picture of banking customers, actionable for both humans and algorithms.
  • Collaborate with business partners to develop meaningful segments for targeted consumer interactions based on shared preferences and behaviors.
  • Partner with machine learning engineers to refine and extend Reinforcement Learning-based marketing optimization capabilities.
  • Main contributor for implementing modern ML solutions to address complex banking use cases, effectively distributing knowledge across the team to promote growth.
  • Create well-organized datasets and data processing, algorithm implementations, and recommended visualizations to support platform software, documentation, feature descriptions, and customer engagement as needed.
  • Proactively guide the team on suitable algorithmic approaches for different problem spaces, enforcing best practices on model training, evaluation, promotion, and monitoring.
Qualifications and Requirements
  • 5+ years' experience delivering applied machine learning or data science capabilities in consumer-facing and/or enterprise applications.
  • Independently prototyped, optimized, validated, managed, operated, and updated machine learning and statistical models.
  • Demonstrable knowledge of statistical inference, experiment design, probability, sampling methodologies, regression, classification, clustering, data mining, multi-armed bandits, time series analysis, causal inference analysis, neural networks, and deep learning techniques.
  • Familiarity with GenAI concepts, including retrieval-augmented generation or fine-tuning.
  • Strong working knowledge of Python-based machine learning frameworks and cloud settings (experience with PySpark and Databricks preferred).

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