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/MLwithin 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 yourGitHub 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
Highlights of our benefits include:-
Paid Time Off: Three weeks of PTO in your first year
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Health Coverage: Competitive medical, dental, and vision insurance to support your well-being
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Retirement Savings: 401(k) plan with an 85% company match on pre-tax and/or Roth contributions, up to IRS limits
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Equity & Investing: Employee Stock Investment Plan (ESIP) with discounted share purchase opportunities
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Learning Education Assistance Program (LEAP): To support your ongoing growth and career advancement
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Employee Investment Benefits: Opportunity to purchase company funds with no sales charge
