Job description

Job Title: Data Analyst (Hybrid)

Location: Toronto, ON

Shift: 9:00 am - 5:00 pm

Job Description

  • Will be responsible for gathering, cleaning, analyzing, and interpreting data from various sources, including client databases, Nielsen, and POS data sets.
  • This role will involve supporting sales projects, ensuring data integrity, and providing valuable insights to stakeholders.

Key Responsibilities

  • Data Collection: Gather data from diverse sources, including databases, spreadsheets, and customer portals.
  • Data Cleaning: Prepare collected data for analysis by identifying and rectifying errors, handling missing data, and mapping data sets to the company hierarchies.
  • Data Analysis: Apply statistical and analytical techniques to interpret data, identify trends, and extract meaningful insights.
  • Project Support: Provide ongoing support to sales projects to maintain data integrity.
  • Reporting: Communicate findings and insights to stakeholders through reports, presentations, and dashboards.
  • Continuous Improvement: Stay updated on data analysis techniques and tools, identify opportunities to enhance analytical processes.

Skills

  • Analytical Skills: Ability to interpret complex data sets and draw meaningful conclusions.
  • Statistical Knowledge: Understanding of statistical methods, such as regression analysis and hypothesis testing.
  • Programming Skills: Proficiency in Python, R, or SQL for data analysis.
  • Data Visualization: Familiarity with data visualization tools like Tableau, Power BI, or Matplotlib.
  • Problem-Solving Skills: Capacity to identify data-related problems and develop innovative solutions.
  • Domain Knowledge: Understanding of the industry or business domain.
  • Communication Skills: Ability to effectively communicate technical findings to non-technical stakeholders.
  • Attention to Detail: Thoroughness in data cleaning and analysis processes.
  • Teamwork: Collaboration with colleagues from different departments.

Education & Qualifications

  • Bachelors degree in Data Science, Statistics, Computer Science, or related field.

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