Data Science Intern

Data Science – Canada | Remote OpportunityWe are hiring on behalf of one of our clients for a Data Science opportunity focused on developing intelligent, data-driven solutions, predictive models, and machine learning applications.

Job Title: Data Scientist

Location: Canada | RemoteRole OverviewThe successful candidate will work with structured and unstructured data to uncover meaningful patterns, develop predictive solutions, and support data-driven business strategies.

This opportunity involves working across the complete data science lifecycle, from data exploration and feature development to model evaluation and deployment.Key ResponsibilitiesExplore large and diverse datasets to identify trends, relationships, anomalies, and potential predictive signals.Define analytical approaches for business and technical problems using statistical and machine learning techniques.Develop, train, test, and optimize supervised and unsupervised machine learning models.Perform feature engineering, feature selection, and data transformation to improve model performance.Design experiments and evaluate different modeling approaches using appropriate statistical methodologies.Build predictive models for areas such as customer behavior, demand forecasting, risk assessment, classification, and business optimization.Conduct exploratory data analysis to understand data quality, distributions, correlations, and underlying patterns.Develop reusable data science workflows and analytical processes using Python or similar programming languages.Evaluate models using appropriate performance metrics and conduct error analysis to identify opportunities for improvement.Apply statistical techniques to validate assumptions and measure the reliability of analytical findings.Work with data engineers and technical teams to prepare datasets and improve data pipelines for machine learning applications.Assist in deploying analytical models into production environments and monitor their performance over time.Identify model drift, data inconsistencies, and other factors that may affect the reliability of deployed solutions.Document data preparation methods, modeling approaches, assumptions, experiments, and results.Communicate technical findings and model outputs to business stakeholders in a clear and understandable manner.Translate business requirements into measurable data science objectives and analytical solutions.Collaborate with product, engineering, business, and analytics teams on data-driven initiatives.Research emerging machine learning techniques and assess their potential application to business problems.Contribute to improving existing models, analytical frameworks, and data science processes.Required SkillsStrong foundation in data science, machine learning, statistics, and data analysis.Proficiency in Python and commonly used data science libraries.Experience working with libraries such as Pandas, NumPy, Scikit-learn, or similar tools.Strong understanding of supervised and unsupervised learning concepts.Ability to work with SQL and relational databases.Understanding of model validation, performance metrics, and statistical evaluation.Strong problem-solving and analytical thinking skills.Ability to work with large datasets and handle data preparation challenges.Good communication skills with the ability to explain technical concepts to non-technical stakeholders.Preferred SkillsExperience with deep learning frameworks such as TensorFlow or PyTorch.Knowledge of natural language processing, time-series analysis, or recommendation systems.Exposure to generative AI, large language models, or AI-powered applications.Familiarity with cloud-based machine learning environments.Understanding of MLOps concepts, model deployment, monitoring, and version control.Experience with tools such as Git, Jupyter, MLflow, or similar platforms.Knowledge of data visualization tools such as Power BI, Tableau, or Python visualization libraries.Familiarity with statistical experimentation, A/B testing, and hypothesis testing.Exposure to APIs, model serving, or integrating machine learning models into applications.Experience working with real-world data science projects or research-based analytical work.What We OfferRemote opportunity supporting data science initiatives in Canada.Opportunity to work on practical machine learning and predictive analytics projects.Exposure to the complete data science lifecycle, from data preparation to model deployment.Opportunity to work with modern AI, machine learning, and analytical technologies.Experience collaborating with multidisciplinary technical and business teams.Opportunities to develop expertise across different data science use cases.Professional growth through hands-on projects involving real-world datasets.Opportunity to strengthen your data science portfolio with practical project experience.