Business Intelligence Analyst - R/Python (6-10 yrs)

Job Description :

A Business Intelligence (BI) Analyst is responsible for transforming raw data into meaningful insights that support strategic decision-making in an organization. The BI Analyst collects, processes, and analyzes data to provide actionable insights that drive business improvements and optimize performance. They work closely with various departments, including finance, operations, marketing, and sales, to identify trends, patterns, and key performance indicators (KPIs).

Key Responsibilities :

1. Data Collection and Analysis :

- Gather and compile data from multiple sources, such as databases, external data, ERP systems, CRM systems, and web analytics tools.

- Conduct thorough data analysis using statistical methods and data visualization techniques.

- Develop and maintain data models, reports, and dashboards to support business operations and strategic decision-making.

2. Reporting and Dashboard Creation :

- Design, develop, and deploy interactive dashboards and reports using BI tools (e.g., Power BI, Tableau, QlikView, Looker).

- Ensure that the dashboards and reports are user-friendly and provide valuable insights to stakeholders.

- Automate report generation and distribution to reduce manual effort and improve accuracy.

3. Data Management and Governance :

- Maintain and optimize the BI data warehouse, including ETL processes to ensure data integrity and accuracy.

- Collaborate with IT and Data Engineering teams to ensure proper data integration and maintenance of data infrastructure.

- Establish data governance practices to maintain data quality and consistency.

4. Collaboration with Stakeholders :

- Work closely with various departments to understand their data needs and provide data-driven insights.

- Participate in meetings with stakeholders to present findings and recommendations.

- Translate business requirements into technical specifications for data analysis and reporting.

5. Data Mining and Predictive Analysis :

- Use advanced analytics techniques, such as predictive modeling and machine learning, to identify trends and forecast future performance.

- Identify patterns and relationships in data to support strategic planning and operational improvements.

6. Performance Measurement and KPIs :

- Develop and track KPIs to measure the effectiveness of business strategies and operations.

- Perform variance analysis and identify root causes of performance gaps.

- Suggest corrective actions based on data-driven insights to improve performance.

7. Continuous Improvement :

- Stay up-to-date with the latest trends and advancements in BI tools and technologies.

- Identify opportunities for process improvements and automation in reporting and analytics.

- Train end-users on BI tools and the effective use of data for decision-making.

8. Ad-hoc Analysis and Reporting :

- Provide ad-hoc reporting and analysis as needed by various departments and senior management.

- Support data requests for strategic initiatives, projects, and operational needs.

Required Skills and Qualifications :

- Bachelor's degree in Computer Science, Data Science, Business Administration, Statistics, or a related field. A master's degree or relevant certifications (e.g., CBIP, Microsoft Certified: Data Analyst Associate) is a plus.

- Proven experience as a BI Analyst or Data Analyst, with a strong background in data analysis and reporting.

- Proficiency in BI tools like Power BI, Tableau, QlikView, Looker, or similar.

- Strong knowledge of SQL for data querying and manipulation.

- Experience with ETL tools (e.g., SSIS, Informatica, Talend) and data warehousing concepts.

- Familiarity with programming languages such as Python or R for advanced data analysis.

- Understanding of data modeling concepts and experience working with relational and non- relational databases.

- Strong analytical and problem-solving skills, with the ability to interpret complex data sets.

- Excellent communication skills, both written and verbal, with the ability to present complex
data findings to non-technical stakeholders.

- Detail-oriented with a commitment to accuracy and quality in data analysis and reporting.

- Ability to work independently and collaboratively in a team environment.

Preferred Skills and Qualifications :

- Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud Platform).

- Knowledge of statistical analysis software (e.g., SAS, SPSS) and machine learning libraries (e.g., scikit-learn, TensorFlow).

- Familiarity with CRM, ERP, and other enterprise systems (e.g., Salesforce, SAP).

- Experience with data visualization best practices and UI/UX principles.

- Knowledge of financial and operational KPIs and experience in a specific industry (e.g., healthcare, finance, retail) is a plus.

Tools and Technologies :

- BI Tools : Power BI, Tableau, QlikView, Looker, Domo, SAP BusinessObjects

- Databases : SQL Server, Oracle, MySQL, PostgreSQL, Snowflake, MongoDB

- ETL Tools : Microsoft SSIS, Talend, Informatica, Alteryx, Apache NiFi

- Data Warehousing : AWS Redshift, Google BigQuery, Microsoft Azure Synapse Analytics

- Programming Languages : SQL, Python, R

- Data Visualization : D3.js, Google Charts, Matplotlib, Seaborn

- Machine Learning and Analytics : Scikit-learn, TensorFlow, PyTorch, SAS, SPSS

- Collaboration Tools : JIRA, Confluence, Microsoft Teams, Slack

- Cloud Platforms : AWS, Microsoft Azure, Google Cloud Platform

- Version Control : Git, GitHub, Bitbucket