Data Analyst

We are seeking a detail-oriented and analytical Data Analyst to join our team. The Data Analyst will be responsible for collecting, processing, and analyzing large sets of data to identify trends, patterns, and insights that can support business decisions. The ideal candidate will be proficient in data analysis tools and have a strong understanding of business operations and KPIs.

Key Responsibilities:
Data Collection and Processing:

Gather and clean large datasets from various internal and external sources.

Ensure data quality and accuracy by identifying and correcting data discrepancies.

Perform data validation and ensure data is properly structured and formatted for analysis.

Data Analysis:

Use statistical techniques and software tools to analyze and interpret data.

Identify trends, patterns, and correlations in complex datasets.

Perform exploratory data analysis (EDA) to uncover insights that can inform business strategies.

Reporting and Visualization:

Create reports, dashboards, and data visualizations to communicate findings to stakeholders.

Use tools like Excel, Tableau, Power BI, or other BI platforms to build visual reports.

Present actionable insights to management and other teams in a clear and concise manner.

Collaboration:

Work closely with cross-functional teams, including marketing, finance, and operations, to understand business needs and provide analytical support.

Provide ad hoc data analysis and insights to support decision-making across various departments.

Continuous Improvement:

Suggest and implement improvements to existing data processes, tools, and techniques.

Stay updated with the latest trends in data analysis, and continuously enhance skills.

Required Skills and Qualifications:
Education:

Bachelors degree in a relevant field (e.g., Data Science, Mathematics, Statistics, Computer Science, Economics, or similar).

Technical Skills:

Proficiency in data analysis tools such as Excel, SQL, Python, or R.

Experience with data visualization tools like Tableau, Power BI, or similar.

Knowledge of statistical techniques (e.g., regression, hypothesis testing, etc.).

Familiarity with data warehousing concepts and ETL processes.

Analytical Skills:

Strong problem-solving skills with a keen attention to detail.

Ability to analyze large datasets and extract meaningful insights.

Experience with exploratory data analysis (EDA) and hypothesis-driven analysis.

Communication Skills:

Strong written and verbal communication skills to present complex data in a simple and understandable manner.

Ability to collaborate with non-technical teams and stakeholders.

Experience:

Previous experience in a data analyst role is often preferred, but entry-level candidates with strong skills may also be considered.