Senior Quantitative Strategist

HuntingCube; Itanagar; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

HuntingCube is seeking a Senior Quantitative Strategist to help design the research architecture, data standards and strategy-development framework for the investment team. You will own significant parts of the first generation of systematic strategies and collaborate with engineers and the founding team to build the operating system for future growth.

You should blend deep quantitative modeling with practical judgement, software discipline and clear communication to explain uncertainty, avoid

Qualifications

• Strong background in quantitative research and investment strategies.
• Experience building and validating trading or investment strategies at scale.
• Excellent communication and collaboration with engineers and business leads.

Responsibilities

• Help define research architecture, data and validation standards.
• Develop strategy-development processes and risk-management practices.
• Lead live monitoring of strategies and governance of models.

Skills

Python

statistics

probability

time-series modelling

cross-sectional modelling

experimental design

empirical finance

portfolio construction

risk-adjusted performance

drawdown

benchmark selection

exposure management

implementation costs

U.S. equity alpha research

factor models

event-driven signals

alternative data

market microstructure

Greeks

implied volatility

open interest

volume

spreads

slippage

options-flow interpretation

ML methods for tabular and sequential

feature stability

calibration

explainability

model monitoring

Research platforms

experiment tracking

cloud infrastructure

APIs

live strategy monitoring

code review

model governance standards

Tools

APIs

Cloud infrastructure

Experiment tracking

Job description

Job Description

Role Overview

Senior Quantitative Strategist - Quantitative Research We are looking for a Senior Quantitative Strategist to play a foundational role in our investment division. You will help determine the research architecture, data and validation standards, strategy-development process, portfolio construction framework and risk-management practices. You will own meaningful parts of the first generation of systematic strategies and help create the operating system future team members will use. This role suits a practitioner who combines quantitative depth with practical judgement, software discipline and clear communication. You should be comfortable building in an early-stage environment, explaining uncertainty, rejecting attractive but fragile results and partnering directly with the founding team and engineers.

What you will do

Key Skills

• Python
• statistics
• probability
• time-series modelling
• cross-sectional modelling
• experimental design
• empirical finance
• portfolio construction
• risk-adjusted performance
• drawdown
• benchmark selection
• exposure management
• implementation costs
• U.S. equity alpha research
• factor models
• event-driven signals
• alternative data
• market microstructure
• Listed equity options
• Greeks
• implied volatility
• open interest
• volume
• spreads
• slippage
• options-flow interpretation
• ML methods for tabular and sequential market data
• feature stability
• calibration
• explainability
• model monitoring
• Research platforms
• experiment tracking
• cloud infrastructure
• APIs
• live strategy monitoring
• setting up or leading research
• code review
• model governance standards

Required Skills

['Python', 'statistics', 'probability', 'time-series modelling', 'cross-sectional modelling', 'experimental design', 'empirical finance', 'portfolio construction', 'risk-adjusted performance', 'drawdown', 'benchmark selection', 'exposure management', 'implementation costs']

Additional Information

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