Senior Research Analyst

Company Description

63 moons technologies limited is driving innovation in the emerging technology landscape with groundbreaking digital ventures. We stand at the forefront of the digital revolution by creating an environment that empowers individuals, businesses, and ecosystems. Our platforms and solutions transform possibilities into realities and are designed to expand horizons.

Role Summary:

Lead research in quantitative strategies for crypto and multi-asset markets. Apply advanced econometrics, time-series modelling, and quantum-classical methods to generate quality signals and benchmark AI vs QC performance.

Key Responsibilities:

• Analyze

  crypto price action

  , order-book microstructure, and volatility regimes.
• Build, validate & optimize

  features

   using various low latency scales.
• Run

  backtests & simulations

  using both classical and quantum algorithms.
• Study cross-asset correlations

  studies

  .
• Track macro, regulatory, and on-chain events affecting market structure.
• Explore

  quantum algorithms

  for signal generation.
• Publish research notes and insights for the Internal desk.

Key Skills:

• Strong in

  statistics, econometrics, time-series analysis

  .
• Proficiency in

  Python, R (C++ optional)

  .
• Experience with

  crypto APIs

  , tick-level datasets, and factor modeling.
• Experience with

  factor modeling, backtesting, feature engineering

  ,

  quantum ML algorithms

• Knowledge of DeFi protocols, staking, futures, options, perpetuals

  .
• Desirable: exposure to

  quantum algorithms

  (QPCA, QSVM, QAOA).

Education & Qualification:

• Mandatory: Experience:

  6–10 years

  in quantitative research / econometrics / time-series.
• At least

  5+ years

  in

  financial markets (crypto, FX, equities, derivatives)

  .
• Demonstrated ability to deliver validated, tradeable signals.
• M.Stat from

  ISI Kolkata/Delhi

  , or M.A / M.Sc in

  Econometrics / Economics / Quantitative Finance

  from

  DSE, IGIDR, ISI Chennai, Gokhale, Ashoka University

  , or equivalent.
• Alternatively: B.Tech/M.Tech from

  IITs/NITs

  in

  Applied Mathematics, Comp Sci, or EE

  with strong quant research exposure.
•  

• Preferred:

• Ph.D. in Statistics, Econometrics, or Financial Engineering

  .
• CQF / CFA (L1–L2) / FRM for industry credibility.

KPIs:

• Number of validated, profitable signals delivered.
• Feature validation frameworks (classical vs quantum).
• Backtest performance (Sharpe, PnL consistency).
• Research papers/ crypto-market insights published internally.