Data Analyst
Data Analyst
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Job Description
Designation: Data Analyst
Roles and Responsibilities:
Data Analysis and Reporting:
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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.
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Perform adhoc analysis to support business needs and strategic initiatives.
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Interpret data analyze results using statistical techniques and provide ongoing reports
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Develop and implement databases data collection systems data analytics and other strategies that optimize statistical efficiency and quality
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Acquire data from primary or secondary data sources and maintain databases/data systems
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Filter and “clean” data by reviewing computer reports printouts and performance indicators to locate and correct code problems
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Work with management to prioritize business and information needs
Advanced Analytics:
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Apply advanced statistical techniques predictive modeling and machine learning algorithms to drive business outcomes such as pricing strategies risk assessment and customer segmentation.
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Collaborate with data scientists to refine and optimize models for better accuracy and performance.
Data Visualization:
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Create compelling visualizations that communicate complex data insights to nontechnical stakeholders.
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Use tools like Tableau Power BI or similar to design userfriendly interactive dashboards for internal and external stakeholders.
Collaboration:
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Partner with product underwriting and operations teams to identify business problems that can be solved through datadriven solutions.
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Advise leadership on data strategies and help prioritize datarelated initiatives based on business objectives.
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Communicate findings and insights to senior management and other teams effectively.
Data Governance & Quality:
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Ensure that all data used in analysis is accurate consistent and aligned with business requirements.
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Work with data engineers to establish best practices for data collection storage and processing to ensure data integrity and quality.
Process Improvement:
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Continuously identify areas for process improvement and automation in data collection reporting and analysis.
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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: 25 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 Scikitlearn Seaborn
Knowledge of data wrangling data cleaning and preparing datasets for analysis.
Experience with cloudbased 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 nontechnical stakeholders.
Ability to work independently and as part of a crossfunctional team in a fastpaced 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
Employment Type
Full Time
