Job Opportunities API

MerQube is an innovative fintech firm, leading the development of cutting-edge technology for indexing and rules-based investing. MerQube offers design and calculation solutions for complex rules-based strategies. Launched in 2019 in New York and San Francisco by a team of index industry veterans and technology experts, MerQube was created to provide a technology focused alternative. MerQube designs and calculates a wide variety of indices, ranging from thematic to ESG, QIS and delta one, while covering multi-asset, equities, futures as well as options. Leveraging cloud-based architecture and today's most advanced index-tracking technology, MerQube's platform enables its clients to bring ideas to market quickly and efficiently. Position Overview: We are looking for a motivated and technically strong Quantitative Associate to join our growing team in Bangalore. In this role, you will contribute to the modeling, backtesting, and launch of index strategies, with a particular focus on options and systematic investing. You will work closely with the Financial Engineering team, platform engineering teams, and internal stakeholders to build scalable, reliable, and data-driven financial solutions. Key Responsibilities: Develop, model, and backtest new index strategies using Python.  Work with financial data sets to clean, analyze, validate, and prepare data for research and production use.  Create and maintain MerQube-branded financial engines and index strategies.  Support daily and historical index calculations, including testing, validation, and automation.  Work on options-based strategies, including pricing, Greeks, payoff structures, volatility, and portfolio-level applications.  Collaborate with Financial Engineering and Platform Engineering teams to improve calculation workflows and data processes.  Automate recurring tasks related to index research, backtesting, and production calculations.  Review output data, identify issues, and troubleshoot calculation or data-quality problems.  Prepare documentation, analysis summaries, and client/internal support materials when required.  Apply software engineering best practices while building financial models, analytics tools, and scalable calculation workflows.  Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, Finance, Mathematics, Economics, Statistics, Data Science, or a related quantitative field.  Minimum 4–6 years of relevant experience in quantitative finance, index research, financial engineering, or software development Strong programming skills in Python, especially for financial modeling and backtesting.  Good understanding of financial markets, equity markets, derivatives, index products, and systematic investing.  Strong understanding of options, including option pricing, Greeks, volatility, payoff structures, and portfolio applications.  Experience working with large data sets and Python libraries such as Pandas, NumPy, or similar tools.  Exposure to financial data platforms such as Bloomberg, Reuters, FactSet, Morningstar, Axioma, or Barra will be an advantage.  Strong analytical mindset with excellent attention to detail and data accuracy.  Ability to work with cross-functional teams and communicate clearly with both technical and non-technical stakeholders.  Strong interest in the intersection of software, financial markets, and quantitative research. Good to Have Experience with backtesting investment strategies or index methodologies. Exposure to systematic investing, factor models, volatility strategies, or derivatives-based indices. Understanding of cloud-based systems, databases, APIs, or distributed computing concepts. Prior experience in fintech, index providers, or quantitative development/research teams. Familiarity with SQL, Git, or basic software deve