Proclink - Data Analyst (2-4 yrs)

Data Analyst

Key Responsibilities:

- Data Collection & Cleaning: Collect and organize data from various internal and external sources, ensuring data integrity and accuracy.

- Data Analysis: Analyze large datasets to identify trends, patterns, and correlations that inform business strategies.

- Use statistical methods and analytical tools to draw actionable insights.

- Reporting: Create clear, comprehensive reports and dashboards to present findings, trends, and performance metrics to key stakeholders in the business.

- Visualization: Design and develop visualizations (e., graphs, charts, and tables) to help communicate data insights effectively to both technical and non-technical audiences.

- Collaboration: Work closely with business units and cross-functional teams to understand their data needs and provide timely, relevant data analysis to support decision-making processes.

- Data Modeling: Develop and maintain models that improve business processes, forecasting, and decision-making based on historical and predictive data analysis.

- Optimization & Efficiency: Suggest improvements and recommend best practices for data collection, data management, and reporting processes to enhance productivity and efficiency.

- Ad-hoc Analysis: Support the business with ad-hoc analysis, providing quick turnaround insights as needed.

Requirements:

Experience: 2-4 years of experience as a Data Analyst or in a similar role with hands-on experience in data analysis, reporting, and visualization.

Technical Skills:

- Proficient in SQL for querying and analyzing large datasets.

- Hands-on experience with Excel (pivot tables, VLOOKUP, advanced formulas).

- Experience with data visualization tools like Tableau, Power BI, or Google Data Studio.

- Familiarity with Python or R for data manipulation, statistical analysis, or automation is a plus.

- Experience with Google Analytics, Salesforce, or other business intelligence platforms is a plus.

- Analytical Skills: Strong problem-solving skills with the ability to think critically and provide data-driven insights.

- Attention to Detail: Exceptional attention to detail and ability to work with large datasets while ensuring high levels of accuracy.

- Communication Skills: Excellent verbal and written communication skills with the ability to present complex data findings in a clear and concise manner to both technical and non-technical stakeholders.

Education: Bachelor's/masters degree in Computer Science, Statistics, Mathematics, or a related field