Data Analyst (3-5 yrs)

Responsibilities :

- Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies in large datasets.

- Develop and implement data mining techniques to extract valuable insights and actionable intelligence.

- Perform product analytics to track key performance indicators (KPIs), identify areas for improvement, and measure the impact of product changes.

- Analyze customer behavior, market trends, and competitor activities to gain a competitive advantage.

- Develop and maintain dashboards and reports to track key business metrics and communicate findings effectively to stakeholders.

- Design, develop, and maintain data pipelines to extract, transform, and load (ETL) data from various sources into data warehouses and data lakes.

- Ensure data quality and integrity throughout the data lifecycle.

- Develop and implement data governance policies and procedures.

- Apply statistical methods (e.g., regression analysis, hypothesis testing, time series analysis) to analyze data and draw meaningful conclusions.

- Develop predictive models to forecast future trends and identify potential risks.

- Conduct A/B testing and other experiments to evaluate the effectiveness of different strategies.

- Translate business requirements into actionable data analysis plans.

- Collaborate with business stakeholders to understand their needs and priorities.

- Communicate complex data insights in a clear, concise, and impactful manner to both technical and non-technical audiences.

- Build strong relationships with stakeholders across different departments.

Qualifications :

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

Experience : Hands-on experience (typically approx 3- 5 years) carrying out data analytics, data mining and product analytics in complex, fast-paced environments.

Technical Skills :

- Applied knowledge of data analytics and data pipelining tools and approaches across all data lifecycle stages.

- Deep understanding of a few and a high-level understanding of several commonly available statistics approaches.

- Advanced Power BI knowledge.

- Advanced SQL knowledge.

- Advanced scripting experience in R or Python.

- Ability to write and maintain moderately complex data pipelines.

Other Skills :

- Strong business acumen.

- Customer-centric and pragmatic mindset.

- Focus on value delivery and swift execution, while maintaining attention to detail.

- Strong communication and stakeholder management skills.

- Continuous learning and improvement mindset.