Junior Data Analyst: Python/SQL + ML for Insights

Global Connect Technologies; Michigan; Sur place; USD 45 000 - 75 000; Plein temps

Résumé du poste

Global Connect Technologies in the United States is seeking an entry-level Data Analyst with strong Python and SQL skills and a basic understanding of Machine Learning. The candidate will analyze data, identify trends, automate data-related tasks, and support data-driven decision-making.

Responsibilities include data extraction, cleaning, EDA, creating reports and dashboards, and collaborating with cross-functional teams to solve data-related problems.

Qualifications

• Strong Python and SQL foundations.
• Basic understanding of Machine Learning concepts.
• Experience with Pandas, NumPy, and scikit-learn.
• Data cleaning, data visualization, and statistics fundamentals.
• Strong analytical and problem-solving abilities.
• Hands-on projects or internships in data analytics or ML are a plus.

Responsabilités

• Extract, clean, and analyze data using SQL and Python.
• Perform exploratory data analysis (EDA) and identify trends and patterns.
• Apply basic statistical analysis and Machine Learning techniques.
• Build and evaluate predictive models to support business needs.
• Create reports, dashboards, and visualizations to communicate insights.
• Collaborate with cross-functional teams to solve data-related problems.

Connaissances

Python

SQL

ML concepts

Pandas

NumPy

scikit-learn

Data cleaning

Data visualization

Statistics

Analytical

Formation

Bachelor's or Master's degree in CS/DS/Statistics/Engineering or related field

Description du poste

Global Connect Technologies in the United States is seeking an entry-level Data Analyst with strong Python and SQL skills and a basic understanding of Machine Learning. The candidate will analyze data, identify trends, automate data-related tasks, and support data-driven decision-making.

Responsibilities include data extraction, cleaning, EDA, creating reports and dashboards, and collaborating with cross-functional teams to solve data-related problems.