Job Description

Franklin Templeton is hiring an Associate Data Scientist to join its innovative Data Science team in Hyderabad. This exciting opportunity is ideal for fresh graduates and early-career professionals who are passionate about Data Science, Machine Learning, Artificial Intelligence, and Financial Analytics. As an Associate Data Scientist, you will work on advanced analytics projects that help optimize investment strategies, improve portfolio performance, and support data-driven decision-making across global financial markets. Working alongside portfolio managers, research analysts, and technology experts, you will gain hands-on experience with real-world financial datasets while leveraging cutting-edge AI technologies to solve complex business problems. This role offers an excellent platform for candidates seeking a career at the intersection of finance and data science.

In this position, you will be involved throughout the complete data science lifecycle, beginning with data extraction, cleansing, preprocessing, and feature engineering before progressing to predictive model development, validation, deployment, and continuous improvement. You will utilize Python, SQL, Machine Learning algorithms, statistical modeling, and Generative AI technologies to analyze structured and unstructured financial data. The role also provides opportunities to build Natural Language Processing (NLP) applications for research automation, sentiment analysis, and intelligent document summarization while creating interactive dashboards and visualizations that help investment professionals make informed decisions. Your work will directly contribute to improving investment research, portfolio optimization, and risk management initiatives.

Franklin Templeton offers a collaborative, inclusive, and innovation-driven work environment where continuous learning is encouraged. The organization invests heavily in employee development through technical training, certification support, mentoring, and exposure to emerging technologies such as Generative AI, Agentic AI, MLOps, Time-Series Analysis, and Predictive Analytics. Whether you aspire to become a Machine Learning Engineer, AI Specialist, Quantitative Analyst, Financial Data Scientist, or Analytics Consultant, this role provides an excellent opportunity to strengthen your technical expertise while gaining valuable exposure to the global investment management industry. With access to modern tools, experienced mentors, and meaningful projects, you can build a rewarding long-term career in financial data science.

Roles & Responsibilities

• Support the complete data science lifecycle by collecting, cleaning, transforming, validating, and preparing structured and unstructured datasets for advanced analytics and machine learning applications.
• Develop predictive machine learning models using statistical techniques, regression, classification, clustering, and ensemble algorithms to generate valuable insights for investment decision-making.
• Perform feature engineering, exploratory data analysis, and model evaluation to improve prediction accuracy, enhance business intelligence, and optimize portfolio management strategies.
• Design, implement, and enhance Natural Language Processing (NLP) and Generative AI solutions for research automation, financial document summarization, and market sentiment analysis.
• Build interactive dashboards and analytical applications using Python-based visualization frameworks such as Streamlit to communicate findings effectively to portfolio managers and senior stakeholders.
• Collaborate closely with investment professionals, research analysts, technology teams, and business stakeholders to translate complex financial requirements into scalable data-driven solutions.
• Maintain comprehensive documentation for datasets, machine learning models, methodologies, validation results, and deployment processes to ensure transparency, reproducibility, and knowledge sharing.
• Utilize Python and SQL to extract, analyze, manipulate, and process large financial datasets from multiple internal and external data sources efficiently.
• Assist in deploying machine learning models into production environments while monitoring model performance and supporting continuous optimization initiatives.
• Stay updated with the latest developments in Artificial Intelligence, Machine Learning, Financial Analytics, MLOps, Generative AI, and quantitative research to continuously improve technical capabilities.

Requirements & Eligibility

• Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Statistics, Artificial Intelligence, Mathematics, or a related quantitative discipline from a recognized institution.
• 0–2 years of experience in Data Science, Machine Learning, Artificial Intelligence, Data Analytics, or related technical domains. Fresh graduates with strong academic projects are encouraged to apply.
• Strong programming skills in Python with hands-on experience in data manipulation, statistical analysis, machine learning model development, and automation.
• Good knowledge of SQL for querying relational databases, data extraction, transformation, reporting, and analytical processing.
• Practical understanding of machine learning techniques including regression, classification, clustering, ensemble learning, model evaluation, and feature engineering.
• Basic knowledge of Time-Series Analysis, Statistical Modeling, Optimization Techniques, and Predictive Analytics to solve business and financial problems effectively.
• Familiarity with Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, and Agent-based AI frameworks will be an added advantage.
• Understanding of MLOps concepts such as version control, model deployment, monitoring, reproducibility, CI/CD pipelines, and workflow automation is desirable but not mandatory.
• Excellent analytical thinking, communication, presentation, and problem-solving abilities with the capability to explain technical concepts to business stakeholders.
• Interest in Financial Markets, Investment Management, Capital Markets, Portfolio Management, and Risk Analytics, along with a strong willingness to continuously learn emerging technologies.

Expected Salary

The expected salary for the Associate Data Scientist role at Franklin Templeton generally ranges between ₹8 LPA and ₹14 LPA for candidates with 0–2 years of experience, depending on educational qualifications, technical expertise, internship experience, and interview performance. In addition to a competitive salary, employees receive comprehensive benefits including medical insurance, life insurance, employee stock investment plans, educational assistance, transport facilities, wellness programs, professional development opportunities, and extensive technical training to support long-term career growth.

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