Franklin Templeton - Senior Data Scientist

Senior Data Scientist

Description:

About the Department

The Research & Strategy team drives Clarion Partners data, forecasting, and analytical insights to support global real estate investment decisions. The team brings together quantitative researchers, data scientists, and strategists who collaborate across geographies to deepen market understanding and inform investment outcomes.

Joining this group offers exposure to complex commercial real estate datasets, modern analytical tools, and opportunities to contribute to high-impact research that shapes firmwide strategy.

How You Will Add Value

Core Responsibilities

- You will lead technical research supporting global investment decisions.

- You will manage and mentor a growing analytics team in Hyderabad.

- You will design and improve statistical, machine learning, and AI models.

- You will identify meaningful signals from large, noisy datasets.

- You will build and enhance forecasting and ranking models.

- You will apply model outputs to risk and portfolio frameworks.

- You will drive innovation in advanced machine learning and AI.

Strategic Responsibilities

- You will refine and strengthen existing model architectures.

- You will design experimentation and backtesting frameworks.

- You will enhance research platforms and data pipelines.

- You will communicate quantitative insights to global stakeholders.

- You will lead projects with clear objectives and timelines.

Team & Collaboration

- You will coach and grow junior data scientists.

- You will work closely with investment and underwriting partners.

- You will support global teams with analytical insights.

What Will Help You Be Successful

Experience, Education & Certifications

- Masters/Ph.D. in a quantitative discipline.

- 7+ years in data science or quantitative research.

- Experience improving and maintaining forecasting models.

- Strong Python skills and fluency with core libraries.

- Experience with data engineering and SQL.

- Ability to productionize research models.

- Strong communication and stakeholder skills.

Technical Skills

- Knowledge of linear and tree-based ML methods.

- Experience building end-to-end analytical systems.

- Understanding of risk and portfolio modeling.

- Exposure to generative AI and NLP.

- Familiarity with MLOps and model lifecycle tools.

- Experience with Azure, Snowflake, and ETL/orchestration tools.

Soft Skills

- Ability to simplify complex technical concepts.

- Strong project and stakeholder management.

- Collaborative mindset and team orientation.