Junior Data Scientist

Location: Remote (Canada)

Job Type: Full-Time

Experience Level: Entry-Level / Junior

About the Role

• An innovative and data-driven organization is seeking a Junior Data Scientist to support analytics initiatives and deliver actionable insights that drive business impact. This role is ideal for an early-career professional passionate about data, machine learning, and problem-solving.
• The Junior Data Scientist will collaborate with cross-functional teams to analyze complex datasets, develop predictive models, and communicate findings clearly to stakeholders.

Key Responsibilities

• Collect, clean, and preprocess structured and unstructured data from multiple sources
• Perform exploratory data analysis to identify trends, patterns, and anomalies
• Develop and validate predictive and statistical models
• Build dashboards and visualizations to communicate insights effectively
• Assist in deploying machine learning models into production environments
• Document methodologies, processes, and findings
• Support A/B testing, experimentation, and performance measurement initiatives
• Collaborate with engineering, product, and business teams to translate data into strategic decisions

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
• 0–2 years of experience in data analysis or data science (internships included)
• Proficiency in Python or R
• Experience with SQL and working with relational databases
• Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib
• Strong analytical thinking and problem-solving skills
• Excellent communication skills with the ability to explain technical concepts to non-technical audiences

Preferred Qualifications

• Experience with cloud platforms (AWS, Azure, or GCP)
• Knowledge of version control systems (Git)
• Exposure to big data technologies (Spark, Hadoop)
• Understanding of software development best practices