Equity Research - Assistant Vice President
State Street is hiring an Equity Research - Assistant Vice President in Bengaluru, India. Level rates it ; you can apply on State Street.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- The posting mentions NLP among its tools and skills.
- Level classes it as an executive role.
- State Street has 1,100+ other open roles on Level.
- Posted in the last few days.
AI in this role
Location: Bangalore, India
About State Street Investment Management
State Street Investment Management (formerly State Street Global Advisors) is the asset management business of State Street Corporation and one of the world’s largest institutional asset managers, with approximately $6.3+ trillion in assets under management. Founded in 1978 and headquartered in Boston, the firm is the fourth-largest asset manager globally and a pioneer in exchange-traded funds, having launched the first US-listed ETF in 1993. We serve a broad spectrum of clients — from institutional and individual investors to plan sponsors and financial advisors — through a leading global platform spanning indexing, ETFs, and active and quantitative strategies.
SSIM's Investment Solutions Group (ISG) is a team of 100+ investment professionals running more than $500B in multi-asset class portfolios for some of the world's largest, most sophisticated investors. The Bangalore research team is a critically important part of this effort.
Role Overview
This AVP role strengthens the team's capacity to develop implementable research, maintain robust quantitative models and infrastructure, and translate investment insights into portfolio and client applications. The successful candidate will also help embed AI-enabled tools into day-to-day research and contribute to high-quality collaboration across Bangalore, Boston, EMEA and APAC.
Key Responsibilities
- Own Tactical Asset Allocation research workstreams, including idea formulation, data preparation, model development, back-testing, robustness analysis, documentation and implementation support for short- to medium-term multi-asset signals with focus on equity forecasting.
- Develop and improve quantitative frameworks for asset allocation and portfolio construction, with appropriate consideration of transaction costs, risk controls, regime sensitivity and real-world implementability.
- Support the full model lifecycle in Bangalore, including model documentation, validation, production hand-off, monitoring, periodic review and engagement with Model Risk Management and other governance partners.
- Apply AI-enabled tools and modern research workflows, including machine learning, NLP and LLM-based approaches where appropriate, to improve research productivity, insight generation and reproducibility.
- Execute priority research within the global multi-asset agenda, working with senior researchers, portfolio managers and client portfolio managers across regions.
- Partner with and support junior researchers, providing technical guidance, constructive review and knowledge-sharing while remaining accountable for individual deliverables.
- undefined
- Support India research partnerships as needed, contributing analysis, research materials and coordination for joint workstreams.
Qualifications
- Advanced degree (PhD/MS/MBA) in Finance, Economics, Mathematics, Statistics or a related quantitative discipline.
- 7+ years of professional and/or academic experience; CFA designation a plus.
- Experience in quantitative research and modelling for multi-asset portfolios, with demonstrated exposure to developing tactical signals for equity forecasting, including sector and country rotation strategies.
- Demonstrated capability in quantitative analysis — forecasting models, portfolio construction, scenario and risk analysis, and simulation across a range of advanced quantitative techniques.
- Strong quantitative modelling, analytical and programming skills (e.g., Python and/or R, SQL, Excel, VBA).
- Familiarity with financial software and data platforms (FactSet, Bloomberg, Reuters)
- Understanding of model governance, validation and monitoring expectations in a regulated institutional environment is preferred.
- Excellent written and verbal communication skills, including the ability to explain quantitative work to technical, investment and client-facing audiences.
- Ability to work independently, manage multiple stakeholders and collaborate effectively across a globally distributed team.
About State Street
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.
Discover more information on jobs at StateStreet.com/careers
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How we rate this
Equity Research - Assistant Vice President at State Street rates 12 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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