Research Associate supporting DWIHN’s Innovation & Community Engagement team by conducting applied research and informing strategic decisions. Ensuring initiatives are grounded in evidence and reflective of trends and needs in behavioral health.
About the role
- Quantitative Research Analyst enhancing portfolio optimization and tax-aware portfolio construction frameworks at OSAM. Collaborating with teams to translate research insights into production systems for investment strategies.
Responsibilities
- conduct investment research: projects will involve running simulations of investment strategies to determine after-tax effects
- run large-scale simulations and backtests to assess strategy efficacy and after-tax implications
- interact with robust data pipelines and APIs using C#, Python, and SQL, ensuring data quality, reproducibility, and efficient computation
- support integration of research outputs into production portfolio management systems used by PMs and traders
- interface directly with portfolio managers, risk teams, and technology groups to communicate model results, limitations, and implementation details
- apply statistical and machine learning methods (e.g., regression, optimization, NLP, feature engineering) to generate, validate, and enhance alpha factors
Requirements
- Degree in Computer Science, Statistics, Math, Engineering, Physics, or Quantitative Finance
- Master’s or Ph.D. preferred for deeper specialization in quantitative methods, data science, or optimization
- 2-5 years of relevant experience in quantitative research, financial data engineering, or software development for investment applications
- Strong proficiency in C# (or Java), Python, and SQL for data analysis, modeling, and production code
- Experience with object-oriented programming and modular system design in a collaborative environment (Visual Studio, Git)
- Deep understanding of relational databases, schema design, and query optimization
- Expertise in statistical modeling, time-series analysis, feature engineering, and machine learning applications for finance
- Knowledge of portfolio optimization, risk modeling, and factor-based investing
- Familiarity with convex optimization, quadratic programming, and constrained portfolio problems
- Excellent communication skills — able to explain complex quantitative concepts to both technical and non-technical audiences
- Highly organized, detail-oriented, and comfortable managing multiple concurrent research projects
Benefits
- competitive and valuable range of total rewards
- annual discretionary bonus
- 401(k) plan with a generous match
- recognition rewards
- comprehensive benefits package
- range of competitive healthcare options
- insurance
- 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)
- motivational wellbeing program
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