Algorithmic Trader

Role Overview

Seeking an experienced Algorithmic Trading Engineer with deep expertise in futures trading

and algorithmic trading systems to operate, maintain, and enhance a proprietary Renkobased

trading platform for US index futures (ES, NQ, MES, MNQ). This role combines

hands-on coding with real-market execution responsibility.

Location: Remote (India)

Experience: 3–7 years

Type: Contract

About the Trading System

The Trading System is a production-grade algorithmic trading platform that:

Trades ES, NQ, MES, MNQ futures via automated strategies

Uses Renko chart-based logic with dynamic brick sizing

Integrates with Interactive Brokers (IB) for market data and execution

Manages trades via a state machine–driven engine (multiple position states)

Incorporates volatility analysis using VIX/VXN

Includes a full back testing framework against historical tick data

Uses a queue-based execution layer for robust order handling

Key Responsibilities

1. Live System Execution & Operations

Deploy, configure, and run the trading system in paper and live environments

Set up and maintain MySQL schemas, connections, and performance

Configure and monitor IB TWS/Gateway sessions

Oversee live strategy execution during US market hours (9:30 AM–4:00 PM ET)

Monitor system health and ensure near-continuous uptime during trading

Diagnose and resolve issues with connectivity, data feeds, and order execution

2. Strategy Maintenance & Enhancements

Understand and maintain the V221GLi strategy and related versions (V3, V4, V221, etc.)

Adjust parameters based on backtests and changing market conditions

Implement new strategy versions within the existing modular architecture

Debug and fix issues in entry/exit logic, state transitions, and trade management

Optimize Renko brick logic, ATR sizing, and indicator computations

3. Backtesting & Performance Analysis

Run comprehensive backtests using historical data (e.g., historical_ticks)

Analyze results, generate P&L and performance reports, and validate changes

Compare strategy variants and recommend improvements based on data

Produce day-by-day and trade-by-trade analytics and summaries

4. Data Management & Quality

Import and manage historical market data (CSV, Excel, database imports)

Ensure data integrity, handle missing/dirty data, and implement recovery workflows

Maintain real-time data feeds from IB and monitor tick_temp / index_temp tables

Address data synchronization and latency issues

5. Risk Management & Monitoring

Implement and monitor stop-loss, profit target, and position sizing rules

Track unrealized P&L, drawdowns, and risk metrics in real time

Configure alerts (e.g., Slack) for critical events and risk breaches

Enforce risk limits, including after-hours and Friday-close logic

6. Codebase Maintenance & New Features

Refactor and optimize Python code for robustness and performance

Fix bugs and edge cases in data handling and trading logic

Add new indicators, strategy modules, or asset coverage as needed

Maintain documentation and version control hygiene

Write unit tests for core trading and risk functions

Required Technical Skills

Core Technologies

Python 3.9+ (expert)

OOP and modular design

State machine implementations

Async/concurrent programming for real-time systems

SQL/MySQL (advanced)

Schema design and optimization

Complex queries/joins, indexing, and performance tuning

Transaction and connection management

Trading & Analytics Stack

Interactive Brokers API (ibapi) – hands-on experience required

Market data subscriptions

Order routing and execution

Contract and account management

TA-Lib and technical indicators

ATR, EMA, and custom indicators

Pandas / NumPy

Time-series manipulation and analysis

Edicient numeric computations

System & Integration Skills

MySQL setup, tuning, and maintenance

Working with REST APIs and WebSockets

Data formats: CSV, Excel (e.g., xlwings), JSON

Logging, error handling, and runtime monitoring

Required Domain Knowledge

Futures Trading (Must Have)

Strong knowledge of ES, NQ, MES, MNQ futures

Contract specs, tick sizes, multipliers, rollover mechanics

Practical experience (paper or live) with futures execution

US session structure: regular hours, pre-/post-market nuances

Algorithmic Trading Concepts

Renko charts and brick-based strategies

State machine–driven trade lifecycle management

Technical indicators: EMA, ATR, MCO, etc.

Volatility analysis with VIX/VXN

Volume/flow-based conditions and filters

Risk management: stops, targets, position sizing

Backtesting and walk-forward evaluation