Data Analyst/Data Modeler
Role summary
Dice is seeking a Data Analyst/Data Modeler for its client, IT-SCIENT, in Jersey City, NJ. This is a full-time, hybrid role requiring 3 days onsite per week. The position focuses on collaborating with business stakeholders to define data requirements and translate them into technical specifications for canonical data models within the securities finance domain. Responsibilities include analyzing data sources, designing and maintaining data models for trades, positions, collateral, and market data, ensuring data quality, and documenting data definitions. The role involves performing data analysis using SQL, Excel, and potentially Python/R, creating reports and dashboards, and participating in testing and validation. A Bachelor's degree in a relevant field and at least 3 years of experience in data or financial analysis are required, along with strong knowledge of securities finance and proficiency in SQL and advanced Excel.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, IT-SCIENT, is seeking the following. Apply via Dice today!
Role: Data Analyst/Data Modeler
Location: Jersey City, NJ (3 Days onsite/ week)
Full Time position
Job Description:
Need profiles with Trading and Security experience.
Collaborate with business stakeholders to understand data requirements and translate them into technical specifications for canonical data models.
Analyze existing data sources to identify data elements, relationships, and inconsistencies.
Design, develop, and maintain canonical data models and schemas, including positions, trades, collateral, and market data.
Ensure data quality, accuracy, and integrity within the data models, implementing data validation rules and monitoring data flows.
Work closely with data architects, developers, and other analysts to implement data models in various technology platforms.
Document data definitions, data lineage, business rules, and technical specifications for the canonical data models.
Perform data analysis and extract insights from large datasets using tools like SQL, Excel, and potentially Python or R.
Create reports, dashboards, and visualizations to support data governance, data quality, and business understanding of securities finance data.
Participate in testing and validation of data models and data transformations.
Qualifications Required
A Bachelor''''s degree in a relevant field such as Finance, Economics, Computer Science, or Information Systems is required.
Candidates should have at least 3 years of experience in data or financial analysis, preferably within financial services.
A strong understanding of securities finance, including lending, borrowing, and collateral management, is essential.
Required technical skills include proficiency in SQL and advanced Excel for data analysis and modeling.
Experience with data modeling tools and methodologies, as well as familiarity with database concepts, is also necessary.
Essential soft skills include strong analytical and problem-solving abilities with attention to detail.
Excellent communication skills for explaining complex data, and the ability to collaborate effectively in a team environment.
A proactive and continuous learning mindset is also value.
