Data Scientist

• Job description

• Job insights

• Screening questions

• Candidate pipeline

If you post this job on a job board, please do not use company name or salary.

Experience level: Mid-senior

Experience required: 10 Years

Education level: Bachelor’s degree

Job function: Information Technology

Industry: Information Technology and Services

Total position: 1

Relocation assistance: No

Visa sponsorship eligibility: No

Need candidates from Insurance and Financial domain

Job Summary

• Demonstrated skill working directly with stakeholders, business partners, SMEs, systems peers, and cross-functional teams to elicit data requirements and design appropriate data models that align with business needs. Structured execution of data analysis, data profiling, and data mapping tasks.

• Translating current and future business requirements into conceptual, logical, and physical data model designs.

• Proficiency in utilizing standard data modeling tools (e.g. Erwin, ER Studio, Toad DM, Power Designer, etc.).

• Designing data models for multiple distinct patterns (e.g. relational, dimensional, hybrid) associated with data warehouse, BI, and big data applications.

• Creation of new and extension of existing data models across multiple DBMS platforms (e.g. Oracle, SQL Server, DB2, Snowflake, Teradata, NoSQL).

• Ability to understand and explain complex data integration and extraction/transformation/load processes.

• Demonstrated experience identifying and resolving data model performance issues to optimize database performance and enhance overall system functionality.

• Documenting and communicating data model designs and standards to ensure understanding and compliance with expectations for interoperability across the organization.

• Proven communication skills illustrating ability to effectively interact with people at all levels of business and technology organizations.

• Fluency in Python, SQL, and Unix.

• High proficiency with generating complex SQL queries is required.

• Version control of databases and metadata management tools (e.g. Git, Liquibase, etc.).

• Insurance and Financial domain experience is highly desired.

• Experience working in an Agile environment using Lean, Kanban and Scrum practices.