
Head of Quantitative Research
2 days ago
Why are we building Dezerv?
Dezerv is an investment management company that combines the expertise of seasoned investment professionals with advanced technology to provide comprehensive investment management solutions. Our team of experts monitor the performance of portfolios and rebalance them if required to ensure long-term success.
At Dezerv, we aim to deliver:
- Comprehensive assessment of your investment portfolio from India's leading investment experts
- Diversified portfolios to help you create long-term wealth using scientific allocation strategies
- Day-to-day active management of your portfolio and timely corrective actions as and when needed
We are a Series B funded startup and have marquee investors like Premji Invest, Accel, Elevation Capital and Matrix Partners India, as our backers along with Whiteboard Capital & Blume Founders Fund, Kunal Shah of CRED, Varun Dua of Acko, Vidit Aatrey of Meesho, Ashish Mohapatra of OfBusiness, Revant Bhate of Mosaic Wellness are also some of our early investors. Since inception in 2021, our clients have trusted us with over 10000+ crs of their assets.
Key Responsibilities:
- Lead Dezerv's quantitative research strategy and align it with investment objectives
- Develop, test, and iterate quantitative models and strategies end-to-end & conduct data analysis to extract actionable investment insights
- Design algorithms for portfolio construction, optimization, and risk management & ensure compliance with regulatory standards and internal risk protocols
- Manage and mentor a team of quant researchers. Collaborate with the Engineering & Product team to operationalize models
- Present research findings to internal stakeholders and clients & maintain high standards of data quality, model robustness, and research rigor
- Stay current with trends in quant finance, GenAI, and data science and use them to improve our product offerings
Qualifications:
- 7–10+ years of experience in quantitative investment research & data modelling, and a prior experience leading a team of 4-5+ people
- Experience working in the investment domain and ability to create, manage, test, and iterate strategies end to end
- Proficient in Programming languages like Python/R, SQL; experienced with Cloud Data Warehousing technologies like Snowflake, AWS S3, Redshift etc
- Advanced degree in Mathematics, Statistics, Data Science, or related field from a reputed institution, and excellent analytical, communication, and leadership skills
- Strong background in building robust backtesting frameworks to validate strategies using historical data, ensuring reliability and minimizing model risk
- Ability to process and analyse massive datasets efficiently, utilizing modern data engineering and distributed computing tools
- Experience working with engineering, MLOps, and data science teams to deploy models and ensure seamless integration into production environments
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