Jobs in Vaughan

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Within 25 km of Vaughan

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Cognizant

Data Scientist (Hybrid)

Toronto, ON, Canada

The base salary for this position ranges between $75000– $115000 per year. · Full-time

Within 25 km of Vaughan · About 22.9 km from the city centre

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Job details

Pay: The base salary for this position ranges between $75000– $115000 per year.
Job type: Full-time
Apply by: Dec 5, 2026
Posted: Nov 5, 2026

Original job description

Overview

We are looking for a talented and experienced Data Scientist to join our dynamic team. As a Data

Scientist, you will leverage your analytical skills and expertise in machine learning to extract insights from

complex datasets and drive data-driven decision-making across our organization. You will collaborate

closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve

challenging business problems.

Responsibilities

Data Analysis and Exploration

Analyze large, complex datasets to identify trends, patterns, and relationships.
Conduct exploratory data analysis (EDA) to gain insights and formulate hypotheses.
Utilize statistical methods and data visualization techniques to communicate findings effectively.

Predictive Modeling and Machine Learning

Develop and deploy predictive models using machine learning algorithms.
Perform feature engineering, model selection, and hyperparameter tuning to optimize model

performance.

Evaluate model accuracy, precision, recall, and other performance metrics.

Data Mining and Pattern Recognition

Apply data mining techniques to extract actionable insights from structured and unstructured

data.

Identify patterns and anomalies in data to detect fraud, predict customer behavior, or optimize

business processes.

Implement clustering, classification, regression, and other machine learning algorithms as

needed.

Experimentation and A/B Testing

Design and conduct experiments to test hypotheses and validate model assumptions.
Implement A/B testing frameworks to evaluate the impact of changes and interventions.
Analyze experimental results and provide recommendations for further optimization.

Collaboration and Communication

Collaborate with cross-functional teams, including engineers, product managers, and business

stakeholders.

Translate technical findings into actionable insights and recommendations for non-technical

audiences.

Present findings and proposals in clear, concise, and compelling ways.

Requirements

Advanced degree (Master's or Ph.D.) in Computer Science, Physics, Statistics, Mathematics, Economics,

or related field.

Proven experience in data science, machine learning, or predictive analytics roles.
Proficiency in programming languages commonly used in data science (e.g., Python, R, etc.).
Strong understanding of statistical analysis, hypothesis testing, and experimental design.
Experience with machine learning libraries and frameworks (e.g., TensorFlow, scikit-learn,

PyTorch, etc.).

Familiarity with data visualization tools and techniques (e.g., Matplotlib, ggplot, Tableau, etc.).
Excellent problem-solving and analytical skills with attention to detail.
Effective communication and collaboration abilities in a team environment.
Ability to manage multiple projects and prioritize tasks effectively.

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

What you need to have to be considered

List the most important qualifications in descending order
Top 5 most important contributions in descending order
- Only go beyond 5 if absolutely necessary
- Be concise but informative
- Related duties should be combined

These will help you stand out

List the most important nice-to-haves in descending order
Top 5 most important contributions in descending order
- Only go beyond 5 if absolutely necessary
- Be concise but informative

We're excited to meet people who share our mission and can m

an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Total Compensation

We regularly assess market data to ensure we offer a competitive compensation package for our associates. The base salary for this position ranges between $75000– $115000 per year. Where the successful candidate may fall within the range depends on relevant education, work and/or management experience and other business-related and job-necessary qualifications. This position is also eligible for Cognizant’s discretionary annual performance-based bonus, as well as benefits that support your physical, mental and financial wellbeing

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More about this job

Responsibilities

Analyze complex datasets to identify trends, patterns, and actionable insights, and develop, deploy, and evaluate predictive models using machine learning. Design experiments and A/B tests, communicate findings and recommendations to technical and non-technical stakeholders, and collaborate with cross-functional teams to address business problems.

Requirements

Requires a master's or Ph.D. in a relevant quantitative or technical field and proven experience in data science, machine learning, or predictive analytics. Candidates should be proficient in Python or R, statistical analysis and experimental design, machine learning frameworks, and data visualization, with strong analytical, communication, collaboration, and project-prioritization skills.

Skills

Data Analysis
Exploratory Data Analysis
Statistical Analysis
Machine Learning
Predictive Modeling
Feature Engineering
Model Selection
Hyperparameter Tuning
Data Mining
Pattern Recognition
A/B Testing
Experimental Design
Python
R
Data Visualization
Cross-Functional Collaboration

Benefits

Wellbeing Programs
Performance-Based Bonus

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Machine Learning
Predictive Analytics
Exploratory Data Analysis
Statistical Analysis
Hypothesis Testing
Experimental Design
Predictive Modeling
Feature Engineering
Model Selection
Hyperparameter Tuning
Data Mining
Pattern Recognition
Clustering
Classification
Regression
A/B Testing
Python
R
TensorFlow
Scikit-Learn
PyTorch
Matplotlib
Ggplot
Tableau
Data Visualization
Fraud Detection
Anomaly Detection
Customer Behavior
Business Process Optimization

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