Data Scientist – Operations; Infrastructure

Location
:
Toronto

Work Model
: 4 Days Work From Office (WFO)

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Role Overview

The Data Scientist – Intelligent Operations (Infrastructure) is responsible for analyzing infrastructure and IT operations data to identify patterns, root causes, and optimization opportunities.

This role is primarily analytical and experimental, supporting decision-making, strategic planning, and the design of AI-driven operational models. While the Data Scientist does not directly manage production AI systems, they play a critical role in defining system requirements and validating analytical approaches for Intelligent Operations initiatives.

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Core Responsibilities

1. Operations Data Exploration & Analysis

• Conduct in-depth analysis of operational data sources, including:

o Infrastructure metrics

o System logs

o Events

o Incident, problem, and change records

• Identify recurring failure patterns, leading indicators, and operational inefficiencies.

• Provide insights to improve infrastructure performance, reliability, and stability.

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2. Statistical & Machine Learning Modelling

• Develop analytical models for:

o Incident trend analysis

o Root cause pattern identification

o Capacity and demand forecasting

• Collaborate with AI Engineers on:

o Feature engineering

o Model validation

o Ensuring reliability and accuracy of operational analytics

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3. Experimentation & Validation

• Design and evaluate experiments (e.g., A/B testing) to measure the impact of operational changes.

• Assess model accuracy, precision, recall, and false positive rates.

• Validate assumptions behind Intelligent Operations initiatives.

• Promote data-driven decision-making through rigorous experimentation.

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4. Insight Generation & Executive Storytelling

• Translate complex operational datasets into clear, actionable insights.

• Develop executive-ready summaries and dashboards.

• Provide risk and stability indicators to leadership.

• Recommend automation and AI investments based on analytical findings.

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Required Skills & Qualifications

• Strong foundation in:

o Statistics

o Probability

o Machine Learning principles

• Proficiency in:

o Python

o SQL

• Experience working with:

o Time series data

o Logs

o Infrastructure and operational datasets

• Strong communication skills with the ability to present findings to infrastructure teams and senior leadership stakeholders.