Data Analyst

Designation: Data Analyst

Roles and Responsibilities:

 Data Analysis and Reporting:

· Analyze large, complex datasets to extract meaningful insights and provide actionable recommendations.

Develop and maintain regular reports, dashboards, and performance metrics to monitor business KPIs, insurance claims, underwriting performance, and customer insights.

· Perform ad-hoc analysis to support business needs and strategic initiatives.

· Interpret data, analyze results using statistical techniques and provide ongoing reports

· Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality

· Acquire data from primary or secondary data sources and maintain databases/data systems

· Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems

·     Work with management to prioritize business and information needs

 Advanced Analytics:

· Apply advanced statistical techniques, predictive modeling, and machine learning algorithms to drive business outcomes, such as pricing strategies, risk assessment, and customer segmentation.

· Collaborate with data scientists to refine and optimize models for better accuracy and performance.

 Data Visualization:

·     Create compelling visualizations that communicate complex data insights to non-technical stakeholders.

·     Use tools like Tableau, Power BI, or similar to design user-friendly, interactive dashboards for internal and external stakeholders.

 Collaboration:

·     Partner with product, underwriting, and operations teams to identify business problems that can be solved through data-driven solutions.

·     Advise leadership on data strategies and help prioritize data-related initiatives based on business objectives.

·     Communicate findings and insights to senior management and other teams effectively.

 Data Governance & Quality:

·     Ensure that all data used in analysis is accurate, consistent, and aligned with business requirements.

·     Work with data engineers to establish best practices for data collection, storage, and processing to ensure data integrity and quality.

 Process Improvement:

·     Continuously identify areas for process improvement and automation in data collection, reporting, and analysis.

·     Suggest ways to optimize internal workflows and improve data accessibility.

Relevant Experience

 2+ years of experience as a Data Analyst, with at least 2 years in a senior or leadership capacity.

 Experience in the insurance industry or a related sector is highly preferred.

 Strong experience with data analysis tools and programming languages (e.g., SQL, Python, R).

 Proficiency in data visualization tools like Tableau, Power BI, or similar.

No of years of experience:  2-5 Years

Skills & Competencies

Expertise in statistical analysis and predictive modeling.

Strong proficiency in SQL for querying large datasets. Big Query

Programming Language: Python

Python Libraries: NumPy, Pandas, Matplotlib, Scikit-learn, Seaborn

Knowledge of data wrangling, data cleaning, and preparing datasets for analysis.

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

Strong communication skills, with the ability to translate complex data into actionable insights for non-technical stakeholders.

Ability to work independently and as part of a cross-functional team in a fast-paced environment.

Data Visualization: Visualize, analyze and share actionable insights about the data with Microsoft PowerBI, SAS Viya, Knime and IBM Cognos Analytics

Machine Learning: Linear ,and Logistic Regression, Support Vector Machines, Decision Tree, Ensemble Techniques: Bagging, Boosting, Clustering: kmeans and hierarchical. DataModelling, Predictive Modelling

Data Science & Analytics: Predictive Analytics, Text Analytics, Data Modelling, Data Mining, ETLMachine Learning & AI: Machine Learning, Upskilling to Large Language Models and GEN AI

Tools & Frameworks: Git

Operating System: (Linux, Windows)

Microsoft Office: Word, Excel (Advanced), PowerPoint

Project Management & Collaboration: JIRA