Position Description:Leads the implementation of quantitative research projects throughout the Software Development Lifecycle (SDLC) according to a full-stack implementation approach, using R, Python, PL/SQL databases, and AI/ML toolkits. Builds high quality, robust, and efficient analytical and software solutions to improve investment processes. Analyzes information to determine, recommend, and plan installation of a new system or modification or an existing system. Leads the quantitative research team and various investment teams on projects including portfolio construction, risk management, alpha research, and new quantitative product software development. Primary Responsibilities: ·Leads software technology teams leveraging quantitative development best practices.·Develops analytical models using data analytics and software development methodologies.·Applies sophisticated analytics and quantitative concepts to support investment needs and develop new solutions.·Identifies and acquires strategic talent needs, resource planning, and talent allocation across the portfolio.·Delivers high value, scalable, and rapidly developed solutions for Senior Advisers.·Designs, develops, and modifies software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design.·Analyzes user needs and software requirements to determine feasibility of design within time and cost constraints.·Develops and directs software system testing and validation procedures, programming, and documentation. Education and Experience: Bachelor’s degree (or foreign education equivalent) in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and six (6) years of experience as a Director, Quant Development (or related occupation) building high quality, robust, and efficient systems and solutions for financial investment decisions, using R, Python, PL/SQL databases and AI/ML techniques. Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and four (4) years of experience as a Director, Quant Development (or related occupation) building high quality, robust, and efficient systems and solutions for financial investment decisions, using R, Python, PL/SQL databases, and AI/ML techniques.Skills and Knowledge: Candidate must also possess: ·Demonstrated Expertise (“DE”) analyzing and designing systems to build quantitative models for systematic financial investments using R and Python; developing time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research and simulation-based algorithms to build investment strategies using R, Python, MSCI Barra, and Morningstar; and building automated diagnostic reporting processes for model risk management using R and Python.·DE designing and implementing large scale data science projects, Artificial Intelligence (AI) and Machine Learning (ML) models and interfaces using Spark, Tensorflow, Python data science libraries, and Deep Learning (DL) frameworks on Amazon Web Services (AWS) and On-premise computing environments; developing cutting-edge investment tools and strategies using Natural Language Processing (NLP), Large Language Models (LLM), Neural Networks, and Supervised and Unsupervised Learning algorithms.·DE designing and building data analytics life cycle for internal and vendor-based financial markets data using Python, Autosys, and PL/SQL databases; creating complex Extract, Transform, Load (ETL) mechanisms, data models, and performance tuned PL/SQL queries to build data pipelines for standardization, cleansing and aggregating data using Python and Informatica; building algorithms for large scale data processing and investment risk calculations using distributed computing and parallel processing techniques; and building dashboards for alpha and beta performance analysis using Python Dash, R Shiny and Tableau.·DE designing and implementing highly scalable production-ready systems complying with software engineering practices using DevOps tools; performing Continuous Integration (CI) and Continuous Deployment (CD) pipelines (using Linux and Jenkins), code versioning (using Github), batch scheduling (using Autosys and Airflow), and REST APIs (using FAST API and Flask); and creating executables using AWS Lambda, S3, and EC2.Salary: $196,725.00 - $206,725.00/year. #PE1M2