Senior Associate - Portfolio Management, AI

Position Overview:

As a Portfolio Management Senior Associate, AI & Quantitative Solutions at StepStone, you will play a pivotal role at the intersection of quantitative finance and cutting-edge artificial intelligence. This position is central to researching, developing, and implementing AI/Machine Learning solutions across the firm, particularly focusing on Private Equity secondaries use cases and the development of advanced quantitative models. You will transform how we manage portfolios, conduct research, and generate insights. Leveraging diverse data, including complex unstructured formats from private market reporting, to build predictive models and streamline analytical processes that benefit both internal teams and our global client base. This role entails leading initiatives in model testing, validation, and deployment within our liquidity management and portfolio construction frameworks, aligning bespoke solutions with diverse client needs and complex risk/return profiles. You will be a key collaborator with our Data Science, Research, and SPAR teams, driving the acquisition, robust cleaning, and deep understanding of critical data fields to enable advanced AI applications. 

Essential Job Functions:

• AI/ML Model Development & Research: Design, develop, train, and validate advanced AI and Machine Learning models (including Natural Language Processing applications) to solve complex problems in portfolio construction, liquidity management, risk modeling, and performance attribution. 
• Data Engineering for AI Pipelines: Utilize Python, SQL (MySQL), and R for advanced data retrieval, cleaning, transformation, and feature engineering, optimizing data for AI consumption across various sources, including unstructured private market reports (e.g., PDF parsing). 
• Model Deployment & MLOps: Collaborate closely with the web development group to integrate and deploy AI/ML solutions into production environments. 
• Quantitative Research & Backtesting: Conduct rigorous quantitative research, model backtesting, and scenario analysis to assess model performance, robustness, and limitations against varied financial problem statements. 
• Communication & Collaboration: Effectively communicate complex AI model outputs, assumptions, limitations, and strategic implications to both technical and non-technical stakeholders, including senior management and external clients. This involves fostering strong relationships with key internal teams, by actively listening to their needs, and proactively identifying how technology can enhance their workflows and adoption. Engage in thought leadership regarding the merits of new AI applications and analytical approaches. 
• Innovation & Strategic Impact: Demonstrate an independent and efficient working style, consistently translating high-level strategic ideas and business challenges into actionable, AI-driven solutions and model outputs that deliver tangible impact across the firm. 
• Continuous Learning: Stay abreast of the latest advancements in AI, machine learning, and quantitative finance, proactively identifying opportunities for their application within private markets. 

Qualifications:

• Bachelors, Master’s degree or Ph.D. in a highly quantitative field such as Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Econometrics, or a related discipline. 
• 6-8 years of experience in quantitative research, AI/Machine Learning model development, risk modeling, portfolio construction, or performance attribution at a financial institution. 
• Excellent written communication and presentation skills, with the ability to articulate complex technical concepts to a diverse audience. 
• Willingness to work a flexible schedule.
• High level of confidentiality.

Required Knowledge, Skills, and Abilities:

• Deep proficiency in Private Market investments and advanced financial modeling, including quantitative model development and application. 
• Expertise in machine learning and deep learning algorithms, statistical modeling, Natural Language Processing (NLP), and numerical algorithms. 
• Advanced proficiency in Python (including libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL. Experience with AI/ML lifecycle platforms (e.g., Kubeflow, AWS SageMaker, Azure ML) and MLOps best practices for model versioning, testing, and deployment. 

Salary Range: $125,000 - $145,000

The salary range is an estimate of pay for this position.  Actual pay may vary depending on job-related factors that can include location, education, skill, and experience.  The salary range does not include any benefits or other forms of possible compensation that may be available to employees.