Data Scientist- Data Engineering -Toronto, ON - Hybrid - 3 days Onsite

Job Title: Data Scientist & Data Engineer

Location:Toronto, ON - 3 days onsite

Job Summary:

We are seeking a talented and versatile Data Scientist & Data Engineer to join our growing team. This hybrid role combines both data engineering and data science responsibilities, enabling the successful candidate to design and build data pipelines, integrate complex datasets, and develop advanced analytical models to drive data-driven decision-making across the organization. You will work closely with stakeholders to identify business challenges and provide actionable insights, as well as ensure the infrastructure is in place to scale analytics.

Key Responsibilities: Data Engineering Responsibilities:

• Data Pipeline Design & Development: Build and maintain scalable data pipelines to process large datasets from multiple sources, ensuring efficient, accurate, and real-time data flow.
• Data Integration: Develop ETL (Extract, Transform, Load) processes to integrate structured and unstructured data from diverse sources such as APIs, databases, and flat files.
• Data Storage & Management: Design and implement data storage solutions (e.g., relational databases, data lakes, cloud data platforms) optimized for performance and scalability.
• Automation: Automate repetitive tasks related to data collection, cleaning, and processing using tools such as Python, Apache Airflow, or other orchestration tools.
• Data Quality & Governance: Implement data quality checks and data governance practices to ensure the reliability and integrity of data used for analysis.

Data Science Responsibilities:

• Data Exploration & Analysis: Perform exploratory data analysis (EDA) to understand data patterns, trends, and relationships, and prepare data for modeling.
• Statistical Modeling & Machine Learning: Develop and deploy machine learning models, including regression, classification, clustering, and time-series forecasting, using tools like Python, R, or Spark.
• Model Evaluation & Optimization: Evaluate model performance using appropriate metrics (e.g., accuracy, AUC, RMSE) and optimize models for better performance.
• Data Visualization: Create clear and interactive visualizations (e.g., using Tableau, Power BI, or Python libraries like Matplotlib/Seaborn) to communicate insights to stakeholders.
• Collaboration: Work closely with business teams to understand their needs, translate them into data problems, and develop actionable insights to drive business outcomes.

Qualifications:

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, or related field.
• Experience:
  • 3+ years of experience working as a Data Scientist, Data Engineer, or similar roles.
  • Proven experience in building and managing data pipelines.
  • Strong experience with machine learning algorithms and data modeling.
  • Familiarity with data visualization techniques and tools.
• Technical Skills:
  • Proficiency in programming languages such as Python, SQL, Java, or Scala.
  • Experience with cloud platforms like AWS, Google Cloud, or Azure.
  • Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).
  • Experience with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, or similar.
  • Strong SQL skills for querying relational and NoSQL databases.
  • Knowledge of version control systems (Git).
  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.
• Soft Skills:
  • Strong analytical and problem-solving skills.
  • Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.
  • Ability to work collaboratively in cross-functional teams.
  • Self-driven with the ability to work in a fast-paced, dynamic environment.

Preferred Qualifications:

• Experience with real-time data streaming and analytics.
• Familiarity with data governance and security best practices.
• Experience with A/B testing or experimental design.

Benefits:

• Competitive salary and performance-based bonuses.
• Health, dental, and vision insurance.
• 401(k) with company match.
• Flexible work hours and remote work options.
• Professional development opportunities.
• Collaborative and inclusive work culture.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.