Senior Analyst - Fund Analytics

Total 4 + years of experience, with 2+ years of experience in a Quantitative Analyst.

Must have skills:

Quant Background:

- Python Programming Skills

- Investment experience

- AI/Machine Learning Experience

What you will need to succeed in the role:

- B.Tech, MBA, M.Sc in finance, mathematics, statistics, physics or engineering.

- Pursuing or completed CFA or CQF would give you an added advantage.

- At least 4+ years of work experience in financial industry ideally in wealth management, private bank, asset management.

- Practical and proven experience around quantitative and machine learning techniques.

- Must have experience in Python, SQL, VBA, and Excel.

- Familiar with GitHub, html script would give you an added advantage.

- Working knowledge of data modeling and data warehousing techniques is desirable, knowledge of research tools/databases such as Morningstar, Factset, Bloomberg would be of added advantage.

- Exceptional analytical proficiency and problem-solving skills.

- Ability to communicate complex concepts clearly and effectively.

- Team player, strong organizational and time management skills.

Principal responsibilities

- Quantitative fund analytics is already an integral part of the fund selection process. To enhance and build our quantitative due diligence capabilities, we are looking for a self-starter individual with strong academic background, well versed in data analytics and with relevant experience developing end to end solution in Python.

- The individual should have understanding of financial markets and quantitative techniques for data analytics and processing, to help us employ them to solve real-world investment problems.

- Your role as an individual contributor will involve developing various technical solutions used in the mutual fund due diligence process, and may also involve analyzing structured and unstructured data sets to assess fund performance and risk.

- An entrepreneurial, start-up approach and willingness to take end-to-end ownership are crucial, as is the ability to collaborate and communicate with the team members and key stakeholders across the business.

- Support the GMS team by providing accurate data in a timely manner.

- Build first class quantitative tools that are scalable for use across the GMS team.

- Taking up end to end ownership for project from designing till documentation for various automation projects around fund analytics.

- Creation and maintenance of quantitative screens on a periodic basis for analysis of funds under coverage.

- Design and deploy machine learning algorithms for quantitative analysis (e.g., clustering, anomaly detection).

- Implement cutting-edge quantitative technologies through rigorous research and testing.

- Publishing of deliverables such as Monthly Performance Monitoring, One Pager, KFF etc.

- Work on sub stream of the projects for the design, development, enhancement and testing of quantitative models for selecting funds.

- Acquiring data from primary or secondary data sources and maintaining databases, performing data validation checks as per the requirement of the projects and creating automated framework for future use.

- Identify valuable data sources and automate data collection and pre-processing processes.

- Present information using data visualization techniques.

- Conduct empirical analysis related to factors, liquidity, intrinsic risk characteristics, scenario dependencies to ensure thoroughly detailed quantitative research