Associate Data Scientist | Franklin Templeton | Hyderabad

Job Description

Franklin Templeton is hiring Associate Data Scientists for its Hyderabad office. This opportunity is ideal for recent graduates and early-career professionals who are passionate about Data Science, Machine Learning, Artificial Intelligence, Python, SQL, and Analytics.

As an Associate Data Scientist, you will work with financial datasets, build machine learning models, develop AI-powered solutions, and collaborate with investment and technology teams to generate data-driven insights. This role offers hands-on experience across the complete data science lifecycle while working on real-world investment and financial analytics problems.

𝐂𝐨𝐦𝐩𝐚𝐧𝐲: Franklin Templeton
𝐑𝐨𝐥𝐞: Associate Data Scientist
𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: Hyderabad, Telangana
𝐉𝐨𝐛 𝐓𝐲𝐩𝐞: Full-Time
𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 0–2 Years

𝐀𝐛𝐨𝐮𝐭 𝐅𝐫𝐚𝐧𝐤𝐥𝐢𝐧 𝐓𝐞𝐦𝐩𝐥𝐞𝐭𝐨𝐧

Franklin Templeton is a global investment management company offering asset management, wealth management, and fintech solutions. With teams across the world, the company leverages data, technology, and innovation to help clients achieve their financial goals. Franklin Templeton provides an inclusive work culture where employees collaborate on cutting-edge technologies, data-driven decision-making, and AI-powered investment solutions.

𝐉𝐨𝐛 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

As an Associate Data Scientist, you'll support the complete data science lifecycle—from collecting and preparing data to developing, validating, and deploying machine learning models. You'll also work on Generative AI, NLP, predictive analytics, and visualization projects that help investment teams make informed decisions.

This role is an excellent opportunity for candidates looking to build expertise in Data Science, Machine Learning, AI, and Financial Analytics.

Roles & Responsibilities

• Work on the complete data science workflow, including data collection, cleaning, feature engineering, model development, validation, and deployment.

• Analyze financial and business datasets using Python, SQL, and statistical techniques to uncover meaningful insights.

• Build and improve machine learning models that support investment research, portfolio analysis, and risk management.

• Develop AI-powered solutions using Natural Language Processing (NLP) and Generative AI for tasks such as document summarization and sentiment analysis.

• Create interactive dashboards and visualizations using tools like Python Streamlit to communicate insights effectively.

• Collaborate with portfolio managers, research analysts, and engineering teams to solve real business problems.

• Document models, methodologies, and workflows to ensure reproducibility and knowledge sharing.

• Continuously explore new machine learning techniques, AI tools, and data science best practices.

Qualifications & Eligibility

• Bachelor's or Master's degree in Engineering, Data Science, Statistics, or a related field.

• 0–2 years of experience in Data Science or related roles.

• Exposure to financial datasets is a plus but not mandatory.

• Certifications such as CFA, CQF, or FRM are an added advantage.

Skills Required

• Strong programming skills in Python and SQL.

• Understanding of Machine Learning algorithms including regression, classification, clustering, and ensemble methods.

• Basic knowledge of statistics, time-series analysis, and predictive modeling.

• Familiarity with data preprocessing and feature engineering.

• Exposure to NLP and Generative AI concepts.

• Understanding of data visualization and dashboard development.

• Awareness of MLOps concepts is an added advantage.

• Good analytical, problem-solving, and communication skills.

𝐖𝐡𝐲 𝐉𝐨𝐢𝐧 𝐅𝐫𝐚𝐧𝐤𝐥𝐢𝐧 𝐓𝐞𝐦𝐩𝐥𝐞𝐭𝐨𝐧?

• Work on real-world AI and Machine Learning projects in the financial domain.

• Gain hands-on experience with predictive analytics, NLP, and Generative AI.

• Collaborate with experienced investment professionals and data scientists.

• Learn modern data science workflows and industry best practices.

• Build expertise in financial analytics and AI-driven decision-making.

• Excellent learning, mentorship, and career growth opportunities.

𝐂𝐚𝐫𝐞𝐞𝐫 𝐆𝐫𝐨𝐰𝐭𝐡 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬

This role provides a strong foundation for long-term careers in Data Science, Artificial Intelligence, and Financial Analytics.

Potential career paths include:

• Data Scientist

• Machine Learning Engineer

• AI Engineer

• NLP Engineer

• Quantitative Analyst

• Financial Data Scientist

• Analytics Engineer

• MLOps Engineer

• Senior Data Scientist

• AI Solutions Architect

The experience gained in this role can help you build expertise in Machine Learning, Generative AI, Predictive Analytics, Financial Modeling, and Enterprise AI Solutions.

𝐖𝐡𝐨 𝐒𝐡𝐨𝐮𝐥𝐝 𝐀𝐩𝐩𝐥𝐲?

• Fresh graduates and early-career professionals passionate about Data Science.

• Candidates with Python, SQL, and Machine Learning knowledge.

• Individuals interested in AI, NLP, and Generative AI technologies.

• Students with academic, internship, or personal Data Science projects.

• Professionals looking to build a career in AI-powered financial analytics.