Data Analyst
Category: Data Entry Specialist
Job Description
The Data Analyst at Lahore Financial Services is responsible for collecting, processing and analyzing data inside and outside the company, providing data-driven insights and recommendations to support company decision-making and strategy formulation. This position requires proficiency in data analysis tools and techniques, and the ability to extract valuable information from large amounts of data to help the company optimize business processes and improve operational efficiency.Job Skills
Job Requirements:
Education:
Bachelor degree or above, preferably in data science, statistics, computer science, mathematics or related majors.
Work Experience:
1-3 years of work experience in data analysis or related fields.
Experience in the financial services industry is preferred.
Skills:
Proficiency in data analysis tools and programming languages (such as Excel, SQL, Python, R).
Excellent statistical analysis and data modeling skills.
Strong data visualization and report writing skills.
Personal Qualifications:
Good problem-solving and critical thinking skills.
Detail-oriented, able to work efficiently in a fast-paced environment.
Good communication skills, able to clearly convey complex data analysis results to non-technical personnel.
Questions
Main Responsibilities:
Data Collection and Processing:
Collect and organize data sources inside and outside the company to ensure data accuracy and completeness.
Perform data cleaning and pre-processing to ensure data quality.
Data Analysis and Modeling:
Use statistical analysis and data mining techniques to conduct in-depth analysis of data and identify trends and patterns.
Build and maintain data models for forecasting and trend analysis.
Reporting and Visualization:
Prepare detailed data reports and analysis results for management and relevant departments.
Create data visualization charts and dashboards to help the team understand the data and discover key business indicators.
Business Support:
Work closely with business departments to understand business needs and provide data support.
Participate in discussions on business strategies and projects, and provide data-driven recommendations and solutions.
Tools & Techniques:
Use data analysis tools and programming languages such as Excel, SQL, Python, R, etc.
Maintain and optimize data analysis tools and platforms to ensure their effectiveness and performance.
Data Governance:
Ensure that the data analysis process meets data governance and compliance requirements.
Maintain data security and privacy, and comply with company and legal regulations.