Research Analyst (AI & Digital Asset Solutions) - EG-US

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. Work Schedule & Location Hybrid work schedule. Primary work location: Boston, MA. Secondary work locations: San Mateo, CA; San Ramon, CA; Pasadena, CA. Compensation Annual salary range: $150,000 to $200,000, plus an annual discretionary bonus, depending on location and level of relevant experience. EEO Statement 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, 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. #J-18808-Ljbffr