Franklin Templeton off campus drive Associate Data Scientist freshers apply Full Time NEW

At Franklin Templeton, we’re driving our industry forward by developing new and innovative ways to help our clients achieve their investment goals. Our dynamic and diversified 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 offer opportunities not only to help you reach your potential but also to contribute to our clients’ achievements.

Job Description :

Our Data Science team drives innovation in investment management by applying data science, machine learning, and AI to optimize portfolio strategies and manage investment risk. We collaborate closely with portfolio managers, research analysts, and technology experts to deliver actionable insights that support investment decision-making. Joining us means working in a dynamic, intellectually stimulating environment where you will contribute to data-driven investment decisions while growing your expertise in finance and emerging technologies.

Roles and Responsibilities :

• Support the end-to-end data science workflow, including data extraction, cleaning, feature engineering, model development, validation, and deployment.
• Apply statistical and machine learning techniques to financial datasets, including market data, transactional data, and alternative data sources.
• Build and maintain predictive models and analytical tools to support portfolio management, risk assessment, and investment research.
• Implement and refine NLP and Generative AI solutions for research automation, sentiment analysis, and document summarization.
• Create data visualizations and dashboards (e.g., Python Streamlit) to help communicate insights to portfolio managers, research teams, and senior stakeholders.
• Document methodologies, results, and processes to ensure reproducibility and effective knowledge sharing.

Education & Certifications:

• Bachelor’s or Master’s degree in Engineering, Data Science, Statistics or related field.
• CFA, CQF, or FRM certification is a plus.

Experience:

• 0 – 2 years in data science roles.
• Exposure to financial services data is preferred but not required.

Technical Skills:

• Proficiency in Python and SQL for data extraction, analysis, modeling, and reporting.
• Practical experience building and evaluating ML models (e.g., regression, classification, clustering, ensemble methods).
• Foundational understanding of time-series analysis, statistical modeling, and optimization techniques.
• Awareness of MLOps concepts (e.g., version control, model monitoring, pipeline automation, and reproducible workflows) is a plus but not required
• Hands-on exposure to generative AI and agent-based frameworks

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