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Data Scientist
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Role: Data Scientist
Location: Toronto, ON – Onsite
Contract role
Job Summary:
The candidate will be responsible for analyzing large datasets, developing data-driven solutions, building predictive models, and supporting business decisions through data insights.
Key Responsibilities
- Analyze large and complex datasets to identify trends, patterns, and business insights.
- Develop data science solutions using Python and relevant data science libraries.
- Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
- Develop and optimize data processing pipelines using PySpark.
- Build, test, and validate statistical and machine learning models.
- Work with structured and unstructured data from multiple sources.
- Perform model evaluation, tuning, and performance optimization.
- Collaborate with data engineers, business analysts, and application teams.
- Present analytical findings and model results to technical and business stakeholders.
- Maintain documentation for data models, analysis, methodologies, and processes.
- Monitor model performance and identify opportunities for improvement.
Required Skills
- Strong hands-on experience with Python for Data Science.
- Strong experience with PySpark and distributed data processing.
- Good knowledge of Pandas, NumPy, and Scikit-learn.
- Strong understanding of statistics, data analysis, and machine learning concepts.
- Experience with data preprocessing, feature engineering, and model development.
- Good knowledge of SQL and relational databases.
- Experience working with large datasets and big-data environments.
- Strong problem-solving and analytical skills.
- Good communication and stakeholder management skills.
Good to Have
- Experience with AWS, Azure, or GCP.
- Knowledge of Databricks or other Spark-based platforms.
- Experience with machine learning and predictive analytics.
- Knowledge of ML deployment/MLOps concepts.
- Experience with data visualization tools such as Power BI or Tableau.
- Knowledge of NLP or Generative AI is an advantage.
More about this job
Responsibilities
Analyze complex datasets to identify trends and business insights, and develop data science solutions, processing pipelines, and predictive models. Evaluate and optimize models, communicate findings to technical and business stakeholders, document methodologies, and monitor model performance.
Requirements
Requires strong hands-on Python and PySpark experience, knowledge of Pandas, NumPy, Scikit-learn, statistics, machine learning, SQL, and large-scale data processing. Candidates should have experience with data preparation and model development, along with strong analytical, problem-solving, communication, and stakeholder management skills.
Skills
- Python
- PySpark
- Pandas
- NumPy
- Scikit-Learn
- Statistics
- Data Analysis
- Machine Learning
- Data Preprocessing
- Feature Engineering
- SQL
- Distributed Data Processing
- Model Evaluation
- Problem-Solving
- Communication
- Stakeholder Management
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Science & Research
Keywords
- Python
- PySpark
- Pandas
- NumPy
- Scikit-Learn
- SQL
- Relational Databases
- Data Science
- Data Analysis
- Statistics
- Machine Learning
- Predictive Analytics
- Data Preprocessing
- Feature Engineering
- Exploratory Data Analysis
- Distributed Data Processing
- Big Data
- Structured Data
- Unstructured Data
- Model Evaluation
- Model Tuning
- Data Pipelines
- AWS
- Azure
- GCP
- Databricks
- MLOps
- Power BI
- Tableau
- Generative AI