Keerti Anand — Product Engineer
My broad interests include Optimization, Algorithm Design under uncertainty and Theoretical Machine Learning. My Doctoral research involves designing prediction models to directly optimize the performance of Online Algorithms. At Goldman Sachs, I worked as a model validation quant for fixed income pricing models. Currently at MLP, I work on systematic trading strategies for credit products and relative value in cross-asset trading.
Stackforce AI infers this person is a Fintech expert specializing in quantitative analysis and algorithmic trading.
Location: Newport Beach, California, United States
Experience: 9 yrs 6 mos
Skills
- Quantitative Research
- Portfolio Management
- Quantitative Finance
- Statistical Modeling
- Algorithm Design
- Applied Machine Learning
Career Highlights
- Expert in quantitative finance and algorithm design.
- Proven track record in model validation at Goldman Sachs.
- Strong background in applied machine learning and optimization.
Work Experience
Millennium
Quantitative Trading Analyst (1 yr)
Goldman Sachs
Vice President (2 yrs 7 mos)
Aarohan Finance
Summer Intern (1 mo)
Duke University
Doctoral Student (4 yrs 11 mos)
Tel Aviv University
Visting Researcher (4 mos)
Goldman Sachs
Summer Employee (2 mos)
Altisource Asset Management Corporation
Intern (2 mos)
Student Placement Office,IIT Kanpur
Placement Preparation Coordinator (6 mos)
E-Cell IIT Kanpur
SIP Executive (6 mos)
Education
Doctor of Philosophy - PhD at Duke University
Bachelor of Technology (BTech) at Indian Institute of Technology, Kanpur
High School at Delhi Public School Vasant Kunj
