Data Scientist – Insurance & Financial Services

Responsibilities

• Demonstrated experience working directly with stakeholders, business partners, SMEs, systems peers, and cross-functional teams to gather data requirements and design data models that align with business needs. Skilled in structured execution of data analysis, data profiling, and data mapping tasks.
• Ability to translate current and future business requirements into conceptual, logical, and physical data model designs.
• Proficient in using standard data modeling tools (e.g., Erwin, ER/Studio, Toad Data Modeler, Power Designer).
• Experienced in designing data models for various patterns (e.g., relational, dimensional, hybrid) supporting data warehouse, BI, and big data applications.
• Skilled in creating new data models and extending existing ones across multiple DBMS platforms (e.g., Oracle, SQL Server, DB2, Snowflake, Teradata, No
  
  SQL).
• Strong understanding of complex data integration and ETL processes; able to explain these clearly to both technical and non-technical stakeholders.
• Demonstrated ability to identify and resolve data model performance issues to optimize database functionality and overall system performance.
• Experienced in documenting and communicating data model designs and standards to ensure understanding and adherence across the organization.
• Excellent communication skills, with the ability to collaborate effectively with individuals across all levels of business and technology functions.
• Fluency in Python, SQL, and Unix.
• High proficiency in writing complex SQL queries.
• Experience with version control of databases and metadata management tools (e.g., Git, Liquibase).
• Background in the Insurance and Financial domains is highly desirable.
• Experience working in Agile environments using Lean, Kanban, and Scrum practices.

• Demonstrated experience working directly with stakeholders, business partners, SMEs, systems peers, and cross-functional teams to gather data requirements and design data models that align with business needs. Skilled in structured execution of data analysis, data profiling, and data mapping tasks.
• Ability to translate current and future business requirements into conceptual, logical, and physical data model designs.
• Proficient in using standard data modeling tools (e.g., Erwin, ER/Studio, Toad Data Modeler, Power Designer).
• Experienced in designing data models for various patterns (e.g., relational, dimensional, hybrid) supporting data warehouse, BI, and big data applications.
• Skilled in creating new data models and extending existing ones across multiple DBMS platforms (e.g., Oracle, SQL Server, DB2, Snowflake, Teradata, No
  
  SQL).
• Strong understanding of complex data integration and ETL processes; able to explain these clearly to both technical and non-technical stakeholders.
• Demonstrated ability to identify and resolve data model performance issues to optimize database functionality and overall system performance.
• Experienced in documenting and communicating data model designs and standards to ensure understanding and adherence across the organization.
• Excellent communication skills, with the ability to collaborate effectively with individuals across all levels of business and technology functions.
• Fluency in Python, SQL, and Unix.
• High proficiency in writing complex SQL queries.
• Experience with version control of databases and metadata management tools (e.g., Git, Liquibase).
• Background in the Insurance and Financial domains is highly desirable.
• Experience working in Agile environments using Lean, Kanban, and Scrum practices.

• Proficiency with standard data modeling tools (e.g., Erwin, ER/Studio, Toad DM, Power Designer).
• Experience designing data models across multiple distinct patterns (relational, dimensional, hybrid) for data warehouses, BI, and big data applications.
• Ability to create new and extend existing data models across various DBMS platforms (Oracle, SQL Server, DB2, Snowflake, Teradata, No
  
  SQL).
• Strong understanding of complex data integration and ETL processes.
• Proven ability to identify and resolve data model performance issues to enhance system functionality.
• Ability to clearly document and communicate data model standards to ensure organizational alignment.
• Strong interpersonal and communication skills to interact across all business and technical levels.
• Proficiency in Python, SQL, and Unix.
• High-level expertise in generating complex SQL queries.
• Familiarity with version control and metadata tools (e.g., Git, Liquibase).
• Domain experience in Insurance and Financial Services is highly preferred.
• Hands-on experience in Agile methodologies including Lean, Kanban, and Scrum.