AI Research Analyst (AI & Digital Asset Solutions)

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting edge strategies and deep insights to unlock opportunities for long term wealth creation. Our talented, global teams bring expertise that is both broad and unique. From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success. About AI & Digital Asset Solutions  Financial markets are evolving at a breakneck pace—and so are the capabilities required to stay ahead. Investment teams are increasingly asking two questions: how to apply frontier AI to real investment problems (alpha generation, portfolio construction, risk decomposition, workflow automation), and how to rigorously evaluate digital assets alongside traditional asset classes. AI & Digital Asset Solutions is a newly formed, entrepreneurial research team within Franklin Templeton Investment Solutions (FTIS) focused on answering both. We build practical tools, models, and frameworks that investment teams can use—bridging cutting-edge research and real-world deployment. On the AI side, we design and implement AI-enabled capabilities across the investment lifecycle for FTIS —from agentic workflows and research copilots to enhancements in portfolio construction and client-facing tools—working closely with investment business partners, technology, and central AI teams. As an AI Research Analyst, you will get early exposure to solving real problems at the intersection of the two most exciting forces reshaping finance. Responsibilities: • Work with portfolio management, research, and business development teams to identify opportunities where AI can enhance alpha generation, portfolio construction, risk management, predictive analytics, and client-facing workflows • Translate ambiguous investment problems into well-scoped technical solutions, accounting for real-world constraints, edge cases, and data limitations • Work with central AI and engineering teams to productionize models and deploy them into investment workflows • Help drive adoption of AI tools by communicating results clearly and enabling investment teams to use what you build • Contribute to defining and articulating a firm-wide AI strategy for investment management, including identifying high-impact use cases, establishing best practices, and driving adoption across teams Qualifications: • 2+ years of experience in an applied quantitative field, ideally involving deploying DL/ML within an investment management organization • Advanced degree (MS or PhD) in a technical field such as computer science, machine learning, statistics, mathematics, or a related discipline preferred but not required • Working knowledge of financial markets and investment concepts (e.g., portfolio construction, asset allocation, risk management) is a plus, but not required • Strong programming skills in at least one modern language (e.g., C++, Python, Java, C#, JavaScript), with the ability to quickly learn new languages and frameworks as needed • Experience developing or applying machine learning models (e.g., deep learning, time series modeling, or optimization techniques) in real-world settings • High intellectual curiosity and an entrepreneurial mindset, with a proven ability to quickly learn new concepts and apply them to ambiguous, real-world problems • Demonstrated experience working on open-ended, ambiguous problems, with the ability to independently scope questions, design approaches, and iterate toward practical solutions • Proven experience owning end-to-end development of data or AI solutions, from initial concept and modeling through production deployment and real-world adoption • Strong communication skills with the ability to explain complex quantitative concepts to non-technical stakeholders When Applying: • Please upload your GitHub repository, along with your resume. Work Schedule & Location: • Hybrid work schedule • Primary Work Location: Boston-MA • Secondary Work Locations: San Mateo-CA, San Ramon-CA, Pasadena-CA Compensation Range: Franklin Templeton offers employees a competitive and valuable range of total rewards—monetary and non-monetary — designed to support their well-being and recognize their time, talents, and results. Along with base compensation, employees are eligible for an annual discretionary bonus, a 401(k) plan with a generous match, and recognition rewards. We also offer a comprehensive benefits package, which includes a range of competitive healthcare options, insurance, and disability benefits, employee stock investment program, learning resources, career development programs, reimbursement for certain education expenses, paid time off (vacation / holidays / sick / leave / parental & caregiving leave / bereavement / volunteering / floating holidays) and a motivational well-being program. We expect the annual salary for this position to range between $150,000 to $200,000, plus an annual discretionary bonus, depending on location and level of relevant experience. #ASSOCIATE #LI-Hybrid At Franklin Templeton, we believe your benefits should support your life, your goals, and your future. That’s why we offer a comprehensive Total Rewards package designed to help you thrive both personally and professionally. Highlights of our benefits include: - Paid Time Off: Three weeks of PTO in your first year - Health Coverage: Competitive medical, dental, and vision insurance to support your well-being - Retirement Savings: 401(k) plan with an 85% company match on pre-tax and/or Roth contributions, up to IRS limits - Equity & Investing: Employee Stock Investment Plan (ESIP) with discounted share purchase opportunities - Learning Education Assistance Program (LEAP): To support your ongoing growth and career advancement - Employee Investment Benefits: Opportunity to purchase company funds with no sales charge Franklin Templeton is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.

• 2+ years of experience in an applied quantitative field, ideally involving deploying DL/ML within an investment management organization
• Advanced degree (MS or PhD) in a technical field such as computer science, machine learning, statistics, mathematics, or a related discipline preferred but not required
• Working knowledge of financial markets and investment concepts (e.g., portfolio construction, asset allocation, risk management) is a plus, but not required
• Strong programming skills in at least one modern language (e.g., C++, Python, Java, C#, JavaScript), with the ability to quickly learn new languages and frameworks as needed
• Experience developing or applying machine learning models (e.g., deep learning, time series modeling, or optimization techniques) in real-world settings
• High intellectual curiosity and an entrepreneurial mindset, with a proven ability to quickly learn new concepts and apply them to ambiguous, real-world problems
• Demonstrated experience working on open-ended, ambiguous problems, with the ability to independently scope questions, design approaches, and iterate toward practical solutions
• Proven experience owning end-to-end development of data or AI solutions, from initial concept and modeling through production deployment and real-world adoption
• Strong communication skills with the ability to explain complex quantitative concepts to non-technical stakeholders