Quantitative Research Associate, Fundamental Research (Event-Driven)

Functional Title: Quantitative Research Associate, Fundamental Research (Event-Driven)

Department: Quantitative Research

Location: New York, NY

About Davidson Kempner: Davidson Kempner Capital Management LP is a global investment management firm. Founded in 1983, Davidson Kempner is headquartered in New York and has offices in Philadelphia, London, Dublin, Hong Kong, Shenzhen, Mumbai and Abu Dhabi. Our Firm invests globally and opportunistically across the capital structure, in a variety of credit and equity strategies as well as real assets. We apply our multi-dimensional, research-driven investment process to evaluate and execute a diverse range of transactions across asset classes, geographies, and market cycles. We target complex, global situations where our experience and expertise can unlock value.

We bring together exceptional people from different disciplines and backgrounds who are energized by the challenges of navigating complexity. We look for people who demonstrate exceptional critical thinking skills, innate curiosity, creativity, and embrace diverse viewpoints to calibrate their decisions. These differentiators make our people successful beyond a specific job at Davidson Kempner – but throughout their journey with us over many years.

 

The Role: The Quantitative Research Associate will sit within our centralized quantitative research team and support our fundamental investment teams by delivering data-driven research that the teams will utilize during their decision-making. This role will have a strong research focus, requiring the QR Associate to conduct in-depth analyses using structured/unstructured alternative and traditional datasets. Additionally, the analyst will proactively identify and evaluate new data sources to determine their potential for generating investment insights or addressing critical investment questions. This role involves end-to-end research work, from scoping and data sourcing through analysis and delivery, and is a good fit for someone who is comfortable working independently, takes initiative, and enjoys partnering with stakeholders to translate data into investment insights.

Responsibilities:

• Analyze structured and alternative datasets to deliver actionable insights on companies, sectors, and macro trends for investment teams. Examples include predicting a retailer’s revenues, tracking the recovery in travel, and monitoring the job market for signs of inflection.
• Develop subject matter expertise in specific sectors such as real estate, healthcare, and technology and related data categories like credit/debit card transactions, store locations, and pharmaceutical sales data. Take ownership of new project requests and continuously source/evaluate new datasets in these areas to determine their quality, limitations, and applicability to our investment strategies.
• Proactively identify and conduct independent research in partnership with investment teams on key themes that impact multiple teams, such as AI usage and its impact on software companies, data centers, and the energy grid.
• Tackle ad-hoc, fundamental, event-driven diligence requests from the investment teams, helping to evaluate companies and sectors around key catalysts.
• Develop repeatable tools and processes, writing code to automate analysis and produce consistent analytic outputs, to efficiently clean, explore, and analyze large, complex datasets, applying statistical modeling and as needed, more advanced techniques such as machine learning and LLM-based tools.
• Create and maintain analytics dashboards using data visualization tools like Tableau and Sigma.
• Collaborate closely with our technology, market data, and qualitative investment research teams to ensure seamless integration of quantitative insights into the investment decision-making process.

The Person:

• The successful candidate will have: Bachelor’s, Master’s or PhD degree in a quantitative or analytical discipline such as computer science, applied mathematics, statistics, finance, operations research or a related quantitative field.
• 0–5 years of professional experience as a quantitative researcher, data scientist, or data analyst, preferably at an investment manager, investment bank, or real estate investment firm.
• Strong proficiency in Python, Excel, and SQL. Experience with cloud computing platforms, such as Databricks. Demonstrated ability to leverage generative AI tools to accelerate the research process.
• Experience handling and analyzing large, complex datasets from diverse sources with a proven ability in building mathematical and econometric models to derive insights from data.
• Skilled at data visualization and the creation of advanced analytics dashboards using platforms like Tableau and Sigma.

Candidate Profile:

• Excellent communication and problem-solving skills with the ability to clearly present complex topics to investment teams in both verbal and written form.
• Ability to collaborate effectively across departments in a fast-paced, dynamic environment with evolving priorities.
• Strong intellectual curiosity and eagerness to learn with meticulous attention to detail and a passion for connecting financial and business concepts with quantitative data analysis to drive investment insights.