At Franklin Templeton, we’re advancing our industry forward by developing new and innovative ways to help our clients achieve their investment goals. Our dynamic firm spans asset management, wealth management, and fintech, offering many ways to help investors make progress toward their goals. Our talented teams working around the globe bring expertise that’s both broad and unique. From our welcoming, inclusive, and flexible culture to our global and diverse business, we provide opportunities to help you reach your potential while helping our clients reach theirs.

Come join us in delivering better outcomes for our clients around the world!

About the Department

Franklin Templeton Technology (FTT) drives the technology strategy and delivers innovative technology solutions for Franklin Templeton (FT), a global investment leader delivering innovative multi-asset solutions across public and private markets. FT integrates asset allocation, manager research, and implementation to drive portfolio construction, execution, and strategic oversight. Joining FT means working in a collaborative, growth-oriented environment that values innovation in investment technology.

As a Lead Data Scientist, you will design and implement advanced AI and machine learning (ML) solutions to enhance decision-making and automation. You’ll work with cutting-edge technologies, including Generative AI and large language models (LLMs), supporting FT’s mission to modernize investment processes and insights. Collaboration with data engineers, quantitative researchers, and investment professionals will be key to operationalizing scalable, high-impact AI systems. This position will be located in our San Ramon, CA office; we may consider a remote work location for certain designated areas within the U.S.

How you will add value

Core Responsibilities

• AI & ML Development: 

  • Build, train, and deploy ML and AI models to solve business challenges and improve investment decisions.

  • Apply Generative AI, LLMs, and deep learning to automate analysis and reporting.

  • Implement models using MLOps practices for scalability and reliability.

  • Continuously monitor and refine performance.

• Data Engineering:

  • Develop automated pipelines for collecting, cleaning, and validating structured and unstructured data.

  • Partner with engineering teams to ensure robust data governance and accessibility.

• Analytics & Insights:

  • Perform statistical and exploratory analysis to uncover trends and opportunities.

  • Use AI-driven analytics to support portfolio construction, risk management, and client insights.

  • Present findings clearly through dashboards and visualizations.

• Collaboration & Innovation:

  • Translate business needs into AI-based solutions in partnership with portfolio managers and product teams.

  • Research emerging AI methods (e.g., retrieval-augmented generation, vector search) and prototype new applications.

  • Contribute to FT’s AI capability development and best practices.

What will help you be successful in this role

Experience, Education & Certifications

• Bachelor’s or Master’s in Computer Science, Statistics, Engineering, or related field

• 2–4 years of experience in data science, AI, or ML (experience with LLMs preferred)

• Strong Python and SQL skills; experience with PyTorch, TensorFlow, or scikit-learn

• Familiarity with AWS, Azure, or GCP; knowledge of MLOps frameworks

• Excellent problem-solving, communication, and cross-functional collaboration skills

Compensation Range: Along with base compensation, other compensation is offered such as a discretionary bonus, 401k plan, health insurance, and other perks. There are several factors taken into consideration in making compensation decisions including but not limited to location, job-related knowledge, skills, and experience. At Franklin Templeton, we apply a total reward philosophy where all aspects of compensation and benefits are taken into consideration in determining compensation. The salary, benefits and variable rewards will reflect the seniority of the position and a competitive market rate. We expect the annual sala