Quant Modeling [Multiple Positions Available]

Duties: Develop frameworks to extract data from multiple sources and apply business rules to generate datasets for end-user consumption.

Design and manage scalable data pipelines to process complex datasets using parallelism, multi-threading, and batch processing.

Enhance pipeline performance and ensure data and logic consistency across platforms.

Perform statistical analysis to interpret data, identify trends, and draw conclusions.

Conduct data exploration and create visualizations to support analysis of large datasets.

Define data models, metadata, and data dictionaries to support analytical exploration.

Execute requirements gathering, design, development, testing, implementation, and support.

Perform user acceptance testing and deliver demos to stakeholders.

Identify data issues and patterns to improve system architecture and code quality.

Lead development activities, communicate timelines and blockers, and coordinate with stakeholders.

Mentor junior team members.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Business Analytics, Data Science, Information Technology, Computer Science, or related field of study plus 3 years (36 months) of experience in the job offered or as Quant Modeling, Data Scientist, Data Engineer, System Engineer, or related occupation.

The employer will alternatively accept a Bachelor's degree in Business Analytics, Data Science, Information Technology, Computer Science, or related field of study plus 5 years (60 months) of experience in the job offered or as Quant Modeling, Data Scientist, Data Engineer, System Engineer, or related occupation.

Skills Required: This position requires (3) years of experience with the following: Developing ETL pipelines for data migration and processing using Python; Optimizing data workflows using Python libraries including Pandas and NumPy; Creating stored procedures and utilizing Windows functions using SQL.

This position requires (1) year of experience with the following: Creating dashboards and reports using data visualization and business intelligence tools including Tableau; Interpreting data, identifying trends, and drawing conclusions using machine learning frameworks including scikit-learn and TensorFlow.

This position requires any amount of experience with the following: Extracting and loading data from AWS, flat files, and Oracle databases using Python and Excel; Building and optimizing data pipelines for datasets using ETL processes and data migration strategies; Modularizing code using object- oriented programming; Performing parallel processing using multi-threading; Enhancing performance using caching techniques; Managing and analyzing data using database systems and frameworks including Oracle PL/SQL and MS SQL Server; Processing and analyzing data using cloud platforms and big data technologies including AWS, Databricks, and PySpark; Leading development activities using Agile methodologies; Tracking deliverables and resolving technical...