Data Analytics Consultant

Key Responsibilities:

1. Data Analysis and Reporting:

- Gather, clean, and analyze data to support business operations and decision-making.

- Design, develop, and maintain custom reports and dashboards using tools like Power BI, Qlik, or similar.

- Ensure data integrity and accuracy in all reports by validating data sources and performing thorough checks.

2. Data Extraction and Transformation:

- Perform data transformation and cleaning using Python for deeper analysis and reporting.

- Automate the extraction, transformation, and loading (ETL) of data using Python scripts or any advanced automation tools to streamline processes.

3. . Artificial Intelligence (AI) Application:

- Apply AI techniques to various business use cases to drive greater efficiency and innovation.

- Develop, implement, and maintain AI models and solutions tailored to business needs, such as process optimization, predictive analytics, or automation.

- Collaborate with cross-functional teams to identify opportunities where AI can add value and streamline operations.

4. Business Intelligence & Insights:

- Work with business stakeholders to define key performance indicators (KPIs) and metrics for reporting.

- Develop and provide ad-hoc reports to various departments based on business needs.

- Create and deliver insights through data visualization to help teams understand trends and patterns.

5. Collaboration and Communication:

- Partner with internal teams to understand their reporting and data analysis requirements.

- Translate complex data sets into clear, understandable reports for non-technical stakeholders.

- Communicate insights and findings effectively, providing recommendations to enhance business outcomes.

6. Process Improvement:

- Identify opportunities to optimize reporting processes through automation and improved data management practices.

- Collaborate with IT and data engineering teams to enhance data architecture for better reporting and analytics.

Qualifications:

1. Technical Skills:

a. Data Analysis: Proficiency in data analysis using Python (Pandas, NumPy) and data extraction and manipulation.

b. Reporting Tools: Experience with reporting and business intelligence tools like Power BI, Qlik, or similar.

c. ETL: Familiarity with ETL processes to automate data integration tasks.

d. Data Visualization: Strong skills in creating visual representations of data for stakeholders.

e. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for data handling.

f. AI & Machine Learning: Experience with AI and machine learning concepts, including implementing predictive analytics or leveraging AI-powered tools for enhanced data insights.

2. Experience:

- 8+ years of experience in data analysis and reporting roles.

- Proven ability to automate reporting processes using Python and SQL.

- Experience working with large data sets and providing meaningful insights from complex data.

- Demonstrated success in delivering accurate, actionable reports to business stakeholders.

- AI: Demonstrated ability to apply AI techniques for data analysis, such as developing predictive models, automating data classification, or enhancing reporting with AI-driven insights.

3. Soft Skills:

- Strong analytical and problem-solving abilities.

- Excellent proficiency in using Microsoft Office Applications (i.e. Excel, Words, PowerPoint, Outlook etc.).

- Excellent communication skills, with the ability to explain complex data in simple terms.

- Attention to detail and a commitment to delivering high-quality work.

- Ability to work collaboratively across teams and manage multiple projects.

4. Preferred Skills:

- Experience with version control systems (e.g., Git).

- Knowledge of statistical analysis and machine learning models.

- Knowledge on Vehicle System

- Familiarity with data governance and best practices for data security.

Qualifications

Graduate/ Post Graduate in Computer Science/ Information Science / Electronics or equivalent