Overview
Full Time
Skills
Project Management
Performance Management
Preventive Maintenance
Management
KPI
Collaboration
Data Engineering
Data Analysis
Modeling
Evaluation
Sourcing
Research
Data Science
Artificial Intelligence
Machine Learning (ML)
Python
SQL
Data Visualization
Microsoft Excel
Reporting
Amazon Web Services
Workflow
Orchestration
Communication
Computer Science
Mathematics
Statistics
Finance
Accounting
Job Details
Objectives and Responsibilities
Skills and qualifications
- Data Infrastructure Management: Efficiently manage, maintain, and expand the existing data infrastructure for tracking company financial and operational KPIs. This includes building and maintaining data pipelines that clean, transform, and aggregate data from various sources.
- Data Engineering Collaboration: Work closely with the data engineering and technology teams to convert and improve existing Python code, deploy it within the company environment, and create data science workflows to ensure efficient maintenance and updates to the data infrastructure.
- Data Analysis and Modeling: Develop and enhance statistics-based data evaluation and analysis tools and models, focusing on identifying correlations, making predictions, and generating forecasts using both proprietary fundamental data and company-reported data.
- Reporting and Alerting Systems: Work closely with the portfolio manager, fundamental analysts, and proprietary research analysts to develop and maintain efficient reporting and alerting systems for timely insights.
- Proactive Data Sourcing: Partner with fundamental analysts to explore, evaluate, and source new data sources that align with the data-driven fundamental research process. Champion best practices and continuous learning in data science. Explore third-party data vendors and attend quantitative conferences to stay abreast of new data sources and emerging data science technologies, including AI and ML applications.
Skills and qualifications
- At least 5 years of experience with Python, SQL, and data visualization/ exploration tools. Demonstrated experience in automating Excel-based reporting and analysis is highly desirable.
- Familiarity with the AWS ecosystem and experience with workflow orchestration tools such as Dagster and Airflow.
- Strong communication skills, capable of explaining technical concepts and business rationales to both technical and non-technical audiences.
- Ability to thrive in a fast-paced environment with multiple concurrent projects and work effectively within a team.
- Doctor's or master's degree in computer science, mathematics, statistics, or a related field.
- Experience in processing fundamental investing data, with foundational knowledge in finance and accounting highly preferred.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.