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AI and Analytics

Bengaluru, Karnataka, India

Job Type


About the Role

An analytics job typically involves leveraging data and statistical analysis to gain insights and make informed business decisions. Here's a general job description for an analytics role:

Position: Analytics Specialist/Analyst/Data Scientist


1. Data Analysis and Interpretation:
- Collect, clean, and organize large datasets from various sources.
- Apply statistical techniques and data mining methods to extract insights.
- Analyze complex data sets and identify trends, patterns, and correlations.
- Interpret findings and communicate actionable recommendations to stakeholders.

2. Reporting and Visualisation:
- Develop and maintain dashboards, reports, and visualisations to present data analysis results.
- Create visually compelling charts, graphs, and presentations to effectively communicate insights.
- Identify key performance indicators (KPIs) and establish reporting frameworks.

3. Predictive Modeling and Forecasting:
- Build predictive models using statistical techniques and machine learning algorithms.
- Develop forecasting models to estimate future trends and outcomes.
- Evaluate model performance and refine models based on feedback and new data.

4. Data-driven Decision Making:
- Collaborate with cross-functional teams to identify business problems and develop analytical solutions.
- Provide data-driven insights and recommendations to support strategic decision making.
- Conduct A/B testing and analyze results to optimize business processes and strategies.

5. Data Management and Quality Assurance:
- Ensure data integrity, accuracy, and consistency throughout the analytics process.
- Develop and implement data governance policies and procedures.
- Identify data quality issues and recommend solutions for improvement.

6. Tools and Technology:
- Utilize various analytics tools, programming languages, and software (e.g., Python, R, SQL, Tableau, Excel).
- Stay updated with emerging trends and advancements in analytics technologies.

7. Collaboration and Communication:
- Collaborate with stakeholders to understand business needs and translate them into analytical requirements.
- Communicate complex analytical concepts and findings to non-technical stakeholders in a clear and understandable manner.
- Work closely with data engineers, IT teams, and other departments to ensure smooth data flow and integration.

8. Continuous Improvement:
- Identify opportunities to enhance data analytics processes and methodologies.
- Stay updated with industry best practices and new analytical techniques.
- Participate in professional development activities, such as attending conferences or completing online courses.



- Bachelor's or Master's degree in a relevant field (e.g., statistics, mathematics, computer science, data science).

- Strong analytical skills and ability to work with large datasets.

- Proficiency in statistical analysis and data visualization tools.

- Experience with programming languages like Python or R.

- Knowledge of machine learning algorithms and predictive modelling techniques.

- Familiarity with data manipulation, querying, and analysis using SQL.

- Excellent problem-solving skills and attention to detail.

- Strong communication and presentation skills to convey complex ideas effectively.

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