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E-commerce Python/SQL Analyst

E-commerce Python/SQL Analyst
Cynet Systems
7 months 2 weeks ago

Job Details

We are looking for Ecommerce Python / SQL Analyst for our client in Mississauga, ON Job Title: Ecommerce Python / SQL Analyst Job Location: Mississauga, ON Job Type: Contract Job Description: Responsibilities:

  • Code Python-based scripts in Blueconic to answer business questions from Ecom Analytics team and Data pod.
  • Write SQL queries that stitch together datasets across multiple data sources.
  • Develop self-service dashboards that enable Analytics team to answer business questions related to consumer data contained within Blueconic.
  • Work with Analytics team to QA/UAT consumer data pulled from Blueconic and other sources as part of requests.

Key Skill Sets:

  • Strong proficiency in Python programming, experience with data manipulation, analysis, and visualization libraries such as Pandas, NumPy, Matplotlib, and Seaborn.
  • Knowledge of statistical analysis techniques and experience with machine learning algorithms is a plus.
  • Ability to write clean, efficient, and well-documented Python code.
  • Familiarity with SQL and experience working with relational databases.
  • Experience with version control systems such as Git.
  • Experience working with CDP and eCommerce data.
  • Previous Blueconic knowledge is not necessary (Alex can provide knowledge transfer support).
  • Comfortable working with data from multiple platforms like Consumer Master (loyalty/subscriptions), Google Analytics (web analytics), Google Tag Manager (tracking and tagging) and Shopify.
  • Can think critically and is comfortable working creatively with custom/non-standard datasets to derive insights.
  • Strong problem-solving skills and the ability to think creatively to derive insights from complex datasets.
  • Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
  • Self-motivated and able to manage multiple tasks and priorities in a fast-paced environment.
  • Expected Resource Allocation + Roadmap: Half-time (20 hours a week) to start but potential for FT.
  • Example Use case: Monster High waterfall analysis 4 hours of coding work + requirements gathering + investigation/QA of data.

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  • Dice Id: 10516350
  • Position Id: ON_EPOS_0422

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