Data Scientist (Hybrid)
- Toronto, ON, Canada
The base salary for this position ranges between $75000– $115000 per year. · Full-time
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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
- Posting language
- English
- Posted
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
Experimentation and A/B Testing
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
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
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.
- Develop and deploy predictive models using machine learning algorithms.
- Perform feature engineering, model selection, and hyperparameter tuning to optimize model
- Evaluate model accuracy, precision, recall, and other performance metrics.
- Apply data mining techniques to extract actionable insights from structured and unstructured
- Identify patterns and anomalies in data to detect fraud, predict customer behavior, or optimize
- Implement clustering, classification, regression, and other machine learning algorithms as
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.
- Collaborate with cross-functional teams, including engineers, product managers, and business
- Translate technical findings into actionable insights and recommendations for non-technical
- Present findings and proposals in clear, concise, and compelling ways.
- Advanced degree (Master's or Ph.D.) in Computer Science, Physics, Statistics, Mathematics, Economics,
- 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,
- 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.
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
- 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
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
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
Categories
- Data & Analytics
- Technology
- Science & Research
- Software
- Consulting
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