Rohit Kumar
Python engineer for production algorithmic trading and market systems: execution systems, multi-venue market data, exchange connectivity, and data-intensive analytics on digital-asset markets.
Builds event-driven Python platforms (asyncio, Redis, PostgreSQL, Pandas/NumPy) for tick pipelines, order life-cycle tooling, pre-trade controls, and execution-quality observability; alpha research background (factor models, backtesting).
Experience
Software Engineer (Python)
Auro Digital
Delhi, IN
Built real-time multi-venue market data and exchange connectivity (WebSocket, FIX, REST): tick-level order books and trades, normalization, Redis pub/sub fanout (∼10 ms batching, TTL freshness) for execution systems, strategies, and analytics consumers.
Shipped vectorized Pandas/NumPy analytics on consolidated books—slippage, liquidity, market microstructure, and sub-second quote generation; tuned in-memory layouts and serialization for high-frequency book updates.
Owned Python execution-system workflows: venue exchange adapters, open/cancel/fill reconciliation, pre-trade risk and precision checks; idempotent create/edit/cancel paths cut manual ops by >60%.
Architected event-driven execution orchestration (asyncio, worker pools) across multi-venue feeds, connectivity, and strategy services with deterministic scheduling and sub-second order lifecycle handling.
Published execution-quality and feed-health metrics to InfluxDB/Grafana; redundant exchange sessions and recovery (99.9%+ uptime) with Sentry/Elastic APM in production.
Deployed Docker/Ansible/AWS stack (PostgreSQL, Redis, market data, execution, routing) across dev/test/prod for live trading and tooling.
Quantitative Research Consultant
WorldQuant
Delhi, IN
Ranked top 10% on WorldQuant WebSim by designing, backtesting, and submitting alpha signals on global equities via factor models and time-series feature engineering on large historical panels.
Built Python research pipelines for cross-sectional ranking, neutralization, and decay tests; validated out-of-sample robustness across market regimes before production submission.
Software Development Intern
ParkSmart Technologies
Delhi, IN
Cut API latency 10% via async Python, PostgreSQL tuning, and profiling; automated Docker CI/CD (+15% deploy frequency).
Education
Indian Institute of Technology Delhi
B.Tech
Relevant coursework: Data Structures and Algorithms, Analysis and Design of Algorithms, Operating Systems, Computer Networks, Computer Architecture, DBMS, Probability, Linear Algebra
Skills
Projects
Multi-Chain DEX Aggregator (Auro Digital)
Production Python smart routing across EVM/Solana liquidity—slippage, price impact, gas, and venue limits—with unified order book and AMM models (constant-product, concentrated liquidity, hybrid pools).
Async Web3/GraphQL/RPC quote engine with caching, rate limits, and connection pooling for reliable pricing under bursty, volatile on-chain markets.
Linux Kernel Systems Programming (Linux v6.2)
Implemented Rate Monotonic and Deadline Monotonic scheduling on Linux 6.2; built a character device driver with spinlocks, mutexes, and interrupt-safe I/O for concurrent kernel workloads.
Technical Skills
Languages & data
Python, Pandas, NumPy, SQL, time-series data
Trading & market systems
Execution systems, exchange connectivity, multi-venue market data, order books, order routing, pre-trade risk, FIX, WebSocket, REST, TCP/UDP, tick data, execution analytics
Backend & concurrency
asyncio, threading, multiprocessing, event-driven architecture, distributed services, REST APIs, profiling and benchmarking
Infrastructure & research
Linux, Docker, AWS, Ansible, Git, CI/CD, PostgreSQL, Redis, InfluxDB, Grafana, Sentry, Elastic APM; backtesting, factor models, alpha signals; Web3, GraphQL, EVM, Solana, DeFi/DEX routing