Data Analyst - Visualization Tools (2-4 yrs)

Job Description :

We are seeking a skilled and detail-oriented Data Analyst to join our Team.

The successful candidate will be responsible for analyzing complex datasets, creating meaningful reports, and providing actionable insights to support business decisions where accuracy and understanding of the data are critical.

Key Responsibilities :

- Analyze and interpret large datasets to identify trends, patterns, and anomalies.

- Develop and maintain interactive dashboards and visualizations using tools like Power BI to effectively communicate data-driven insights to stakeholders.

- Collaborate closely with business stakeholders to understand their data needs and translate them into actionable insights.

- Ensure data quality and accuracy through data cleaning, validation, and transformation techniques.

- Utilize statistical methods and techniques to analyze business performance and identify areas for improvement.

- Develop and maintain data pipelines and processes to ensure data availability and accessibility.

- Stay abreast of the latest data analysis methodologies, tools, and technologies.

- Contribute to the development and improvement of data-driven decision-making processes within the organization.

Required Skills and Experiences :

- 1+ years of experience in data analysis and reporting.

- 1+ years of experience working with Power BI, SQL, and Excel.

- 1+ years of experience working with financial data, with a strong emphasis on loans/lending data.

- Bachelor's degree in a related field (Data Science, Statistics, Computer Science).

- Strong analytical and problem-solving skills with the ability to think critically and independently.

- Excellent communication and presentation skills to effectively convey complex data insights to both technical and non-technical audiences.

- Proficiency in data visualization techniques and tools.

- Strong attention to detail and accuracy.

Preferred Skills and Experiences :

- Experience with Python programming language, including libraries such as Pandas, NumPy, and Scikit-learn.

- Experience with Jupyter Notebooks for data exploration and analysis.

- Knowledge of machine learning concepts and techniques (classification, regression, clustering).

- Experience with cloud-based data platforms (AWS, Azure, GCP).

- Experience with data warehousing and data lake concepts