Data Scientist – Intelligent Operations (Infrastructure)
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Job Location:
Monthly Salary:
Experience Required:
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Location: Toronto
Work Model: 4 Days Work From Office (WFO)
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.
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.
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
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.
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.
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.
Required Skills:
Experience (Years): 8-10
Company Industry
IT Services and IT Consulting
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
