Overview
On Site
Full Time
Skills
Financial Modeling
Analytics
Research
Decision-making
Portfolio Management
Process Automation
Portfolio Optimization
Algorithms
Dashboard
Data Manipulation
Pandas
NumPy
Statistical Models
Time Series
Monte Carlo Method
Data Visualization
Tableau
Microsoft Power BI
Plotly
Dash Python
Modeling
Django
Database Administration
Securities
Writing
Data Analysis
Testing
Management
Debugging
Analytical Skill
Attention To Detail
Strategic Thinking
Knowledge Sharing
Computer Science
Python
Quantitative Analysis
Optimization
Workflow
Training
Human Resources
Science
Economics
Finance
Mathematics
Physics
Statistics
Collaboration
Expect
Accountability
SAP BASIS
Job Details
Job Description Summary
Job Description
As part of the AMS Research team, the Investment Data Scientist plays a key role in developing, improving, and evaluating quantitative models that directly support investment decision-making and portfolio management. This is a hands-on technical role focused on writing production-quality Python code to analyze financial datasets, enhance portfolio construction methods, and automate investment workflows.
You'll collaborate closely with Investment Committee members, analysts, and other stakeholders to improve the investment process through portfolio optimization, statistical modeling, and process automation. You'll also develop interactive dashboards and visualizations that translate complex analytical outputs into actionable insights. This role requires strong analytical thinking, the ability to solve complex technical problems independently and collaboratively, and a commitment to delivering high-quality, validated results.
Essential Duties and Responsibilities
Knowledge, Skills, and Abilities
Core Knowledge (Required):
Preferred Knowledge:
Technical Skills:
Abilities:
Educational and Experience Requirements
Education
Bachelor's: Computer and Information Science, Bachelor's: Economics, Bachelor's: Engineering, Bachelor's: Finance, Bachelor's: Mathematics, Bachelor's: Physics, Bachelor's: Statistics
Work Experience
General Experience - 3 to 6 years
Certifications
Travel
Less than 25%
Workstyle
Hybrid
At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
Grow professionally and inspire others to do the same
Work with and through others to achieve desired outcomes
Make prompt, pragmatic choices and act with the client in mind
Take ownership and hold themselves and others accountable for delivering results that matter
Contribute to the continuous evolution of the firm
At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.
Job Description
As part of the AMS Research team, the Investment Data Scientist plays a key role in developing, improving, and evaluating quantitative models that directly support investment decision-making and portfolio management. This is a hands-on technical role focused on writing production-quality Python code to analyze financial datasets, enhance portfolio construction methods, and automate investment workflows.
You'll collaborate closely with Investment Committee members, analysts, and other stakeholders to improve the investment process through portfolio optimization, statistical modeling, and process automation. You'll also develop interactive dashboards and visualizations that translate complex analytical outputs into actionable insights. This role requires strong analytical thinking, the ability to solve complex technical problems independently and collaboratively, and a commitment to delivering high-quality, validated results.
Essential Duties and Responsibilities
- Develop and maintain robust Python code for portfolio construction, statistical analysis, and automation of investment workflows.
- Design and implement portfolio optimization algorithms.
- Apply advanced statistical methods to extract insights from financial datasets.
- Collaborate with Investment Committee members, analysts, and quant team members to align model development with investment objectives and operational needs.
- Build automated processes to eliminate manual tasks, reduce errors, and improve workflow efficiency.
- Create interactive dashboards and visualizations to communicate analytical findings.
Knowledge, Skills, and Abilities
Core Knowledge (Required):
- Python libraries for data manipulation and array mathematics: pandas, NumPy, SciPy, and optimization libraries such as CVXPY.
- Statistical modeling and optimization: mixed integer programming, regressions, time series, and Monte Carlo simulation.
- Data visualization: Streamlit, Tableau, Power BI, Plotly Dash, or similar platforms.
- Quantitative finance: portfolio construction methods, risk modeling, and financial data analysis.
Preferred Knowledge:
- Financial markets, investment products, and portfolio theory.
- Performance measurement and attribution methodologies.
- Django framework for database management.
- Advanced investment concepts and practices in the securities industry.
Technical Skills:
- Writing clean, documented, and version-controlled Python code.
- Translating business problems into quantitative models and technical solutions.
- Building and maintaining automated workflows.
- Creating clear, intuitive data visualizations for non-technical audiences.
- Validating and testing models to ensure accuracy and reliability.
- Performing performance calculations and financial data analysis.
Abilities:
- Work independently and collaboratively in a fast-paced team environment.
- Deliver accurate, high-quality analytical work through rigorous testing and validation.
- Manage multiple projects with competing deadlines.
- Communicate complex technical concepts clearly to non-technical stakeholders.
- Debug code, validate results, and ensure analytical accuracy.
- Balance attention to detail with strategic thinking.
- Adapt to changing priorities and requirements.
- Learn new quantitative techniques and investment concepts quickly.
- Promote team effectiveness through knowledge sharing and collaboration.
Educational and Experience Requirements
- Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or a related quantitative field.
- 3-6 years of hands-on experience with Python development and quantitative analysis.
- Demonstrated experience building optimization models, statistical systems, and/or automated workflows.
OR - Any equivalent combination of experience, education, and/or training approved by Human Resources.
Education
Bachelor's: Computer and Information Science, Bachelor's: Economics, Bachelor's: Engineering, Bachelor's: Finance, Bachelor's: Mathematics, Bachelor's: Physics, Bachelor's: Statistics
Work Experience
General Experience - 3 to 6 years
Certifications
Travel
Less than 25%
Workstyle
Hybrid
At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
Grow professionally and inspire others to do the same
Work with and through others to achieve desired outcomes
Make prompt, pragmatic choices and act with the client in mind
Take ownership and hold themselves and others accountable for delivering results that matter
Contribute to the continuous evolution of the firm
At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.
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.